USA Today reported that about 20 of all people in the United States.pdf
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USA Today reported that about 20% of all people in the United States are illiterate suppose you take 11 people at random off a city street make a histogram showing the probability distribution of the number of illiterate people out of the seven people in the sample b) find the mean and standard deviation of this probability distribution (round your standard deviation to two decimal places) find the expected number of people in this sample who are illiterate.
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balangtan 70 milyar dolarlk bir iletmeye gemek iin gereken bu mu? Yoksa bu nitelendirmeler,
kskan rakiplerin eletirileri yanl m? Uber ya da dnyann nde gelen ulam hizmetlerinden biri olan
Uber Technologies Inc. olarak bilinen dk maliyetli ara arma hizmetinin heyecanl yolculuuna
uzunca bir gz atalm.
Balarken
2008 ylnda Paris'te bir konferansa katlan teknoloji giriimcileri Garrett Camp ve Travis Kalanick,
karl bir gecede taksi bulmann zorluundan ikayet ediyorlard. Bu dei tokutan, bir dmeye
dokunarak talep zerine bir araba aracak yeni teknoloji yaratma fikri geldi. The Upstarts'ta yazar
Brad Stone, en azndan irketin resmi kken efsanesinin bu olduuna dikkat ekiyor. Aslnda bu fikri
ortaya atan Camp, bir sredir arkada Kalanick ile akll telefon tabanl bir ehir arabas (lks araba veya
siyah araba) paylam hizmeti kavramn tartyordu.
Camp, yelerin favori web sitelerini dier insanlarla paylamalarna olanak tanyan keif ve neri
arama motoru StumbleUpon'un kurucu ortayd. Kalanick ("cal-a-nick" olarak telaffuz edilir) ilk
iini 18 yanda kurdu, bu bir SAT-hazrlk zel ders hizmetiydi. Bir dosya paylam ve hizmet ii olan
Scour, onun ikinci i macerasyd, ancak Kalanick'in byk abasna ve srarna ramen baarsz oldu. Bir
sonraki giriimi, bir video ak giriimi olan Red Swoosh'du. 2007'de 23 milyon dolara satld. Mart
2009'da Camp, Calgary'den eski yksek lisans rencileri Oscar Salazar ve Conrad Whelan ile
birlikte Kalanick'in "mega danman" olarak grev yapt yeni ehir arabas fikrinin denenmesinde ba
ekti. . Bunlardan biri, ilk olarak Haziran 2007'de Apple tarafndan piyasaya srlen ve yalnzca akll
telefon endstrisinde devrim yaratmakla kalmayp ayn zamanda genellikle "paylam ekonomisi"
olarak adlandrlan modern ibirliki ekonomiyi yaratmasyla tannan iPhone iin bir mobil
uygulamann prototipiydi.
Mart 2009'da UberCab olarak kurulan irket, mobil uygulama konseptini ilk olarak New York'ta
test etti, ardndan 2011'de San Francisco'da kullanclarn siyah lks bir araba talep etmek iin
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edebilir ve srcnn konumunu (GPS araclyla) takip edebilirdi. telefonlarnda) ve arabann tam olarak
ne zaman geleceini biliyorlar.
Birka arabas olmasna ve ok az kiinin bunu bilmesine ramen, giriim byk bir hit oldu. 2011 ylnda,
ehir ve eyalet dzenleyicilerinin srar zerine, irket adn UberCab'den (nk bir ehir arabas veya taksi
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experiencia, en el mercado laboral, buscando ferias de carreras universitarias y departamentos de
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//************************** SLL.java *********************************
// a generic singly linked list class
public class SLL {
private class SLLNode {
private T info;
private SLLNode next;
public SLLNode() {
this(null,null);
}
public SLLNode(T el) {
this(el,null);
}
public SLLNode(T el, SLLNode ptr) {
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}
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public SLL() {
head = tail = null;
}
public boolean isEmpty() {
return head == null;
}
public void addToHead(T el) {
head = new SLLNode(el,head);
if (tail == null)
tail = head;
}
public void addToTail(T el) {
if (!isEmpty()) {
tail.next = new SLLNode(el);
tail = tail.next;
}
else head = tail = new SLLNode(el);
}
public T deleteFromHead() { // delete the head and return its info;
if (isEmpty())
return null;
T el = head.info;
if (head == tail) // if only one node on the list;
head = tail = null;
else head = head.next;
return el;
}
public T deleteFromTail() { // delete the tail and return its info;
if (isEmpty())
return null;
T el = tail.info;
if (head == tail) // if only one node in the list;
head = tail = null;
else { // if more than one node in the list,
SLLNode tmp; // find the predecessor of tail;
for (tmp = head; tmp.next != tail; tmp = tmp.next);
tail = tmp; // the predecessor of tail becomes tail;
tail.next = null;
}
return el;
}
public void delete(T el) { // delete the node with an element el;
if (!isEmpty())
if (head == tail && el.equals(head.info)) // if only one
head = tail = null; // node on the list;
else if (el.equals(head.info)) // if more than one node on the list;
head = head.next; // and el is in the head node;
else { // if more than one node in the list
SLLNode pred, tmp;// and el is in a nonhead node;
for (pred = head, tmp = head.next;
tmp != null && !tmp.info.equals(el);
pred = pred.next, tmp = tmp.next);
if (tmp != null) { // if el was found;
pred.next = tmp.next;
if (tmp == tail) // if el is in the last node;
tail = pred;
}
}
}
@Override
public String toString() {
if(head == null)
return "[ ]";
String str = "[ ";
SLLNode tmp = head;
while(tmp != null){
str += tmp.info + " ";
tmp = tmp.next;
}
return str+"]";
}
public boolean contains(T el) {
if(head == null)
return false;
SLLNode tmp = head;
while(tmp != null){
if(tmp.info.equals(el))
return true;
tmp = tmp.next;
}
return false;
}
public int size(){
if(head == null)
return 0;
int count = 0;
SLLNode p = head;
while(p != null) {
count++;
p = p.next;
}
return count;
}
}
Part I: Programming Use the singly linked list class (Given below) to implement integers of
unlimited size. Each node of the list should store one digit of the integer. You are required to
implement the addition, subtraction and multiplication operations. In addition, provide a test
class that will do the following: It will keep asking the user to enter two integers, choose one of
the operations (addition, subtraction, multiplication) and then display the result. The program
will stop upon e.
using IRAC method Mary is an explorer and is about to set off on a.pdf
using IRAC method
Mary is an explorer and is about to set off on a ground-breaking expedition at the Debswana
mines. Rose and John , who are Mary's friends are also professional explorers themselves, they
then entered into a written agreement with each other that they will each help Mary from the
start to the the end of her expedition. John breaks the agreement and does not help Mary to the
end of her expedition, and instead returns home early.
in 250-350 words advise Mary as to whether she can sue John for breach of contract.
USING httpsraw.githubusercontent.comBeeDrHUIntroduction-to-Py.pdf
*USING 'https://raw.githubusercontent.com/BeeDrHU/Introduction-to-Python-CSPC-323-
/main/sales_forecast.csv'
please fix the errors for the RNN using python so the code can run without errors, Thank you*
##Defining Function to Build Multivariate Data Structure
def multivariate_data(dataset, target, start_index, end_index, history_size,
target_size, step, single_step=False):
data = []
labels = []
start_index = start_index + history_size
if end_index is None:
end_index = len(dataset) - target_size
for i in range(start_index, end_index):
indices = range(i-history_size, i, step)
data.append(dataset[indices])
if single_step:
labels.append(target[i+target_size])
else:
labels.append(target[i:i+target_size])
return np.array(data), np.array(labels)
##Define the Multi-step Plotting Structure
def multi_step_plot(history, true_future, prediction):
plt.figure(figsize=(12, 6))
num_in = create_time_steps(len(history))
num_out = len(true_future)
plt.plot(num_in, np.array(history[:, 1]), label='History')
plt.plot(np.arange(num_out)/STEP, np.array(true_future), 'bo',
label='True Future')
if prediction.any():
plt.plot(np.arange(num_out)/STEP, np.array(prediction), 'ro',
label='Predicted Future')
plt.legend(loc='upper left')
plt.show()
##Define Function to Plot training and Validation over Time
def plot_train_history(history, title):
loss = history.history['loss']
val_loss = history.history['val_loss']
epochs = range(len(loss))
plt.figure()
plt.plot(epochs, loss, 'b', label='Training loss')
plt.plot(epochs, val_loss, 'r', label='Validation loss')
plt.title(title)
plt.legend()
plt.show()
##How far into the past do you want the model to see?
past_history=
##How far into the future do you want the model to see?
future_target=
##
STEP=
df_val = len(dataset) - past_history - future_target
x_train_multi, y_train_multi = multivariate_data(dataset, dataset[:, 1], 0,
df_train, past_history,
future_target, STEP)
x_val_multi, y_val_multi = multivariate_data(dataset, dataset[:, 1],
df_train, df_val, past_history,
future_target, STEP)
##Define Constants
BATCH_SIZE =
BUFFER_SIZE =
EPOCHS =
EVALUATION_INTERVAL =
##Adding Layers Due to Complexity
train_data_multi = tf.data.Dataset.from_tensor_slices(())
train_data_multi = train_data_multi.cache().shuffle().batch().repeat()
val_data_multi = tf.data.Dataset.from_tensor_slices(())
val_data_multi = val_data_multi.batch().repeat()
multi_step_model = tf.keras.models.Sequential()
multi_step_model.add(tf.keras.layers.LSTM())
multi_step_model.add(tf.keras.layers.LSTM())
multi_step_model.add(tf.keras.layers.Dense(72))
multi_step_model.compile(optimizer=tf.keras.optimizers.RMSprop(clipvalue=1.0), loss='mae')
##Train the Model
multi_step_history = multi_step_model.fit(train_data_multi, epochs=,
steps_per_epoch=,
validation_data=,
validation_steps=50)
##Predict Future Data
for x, y in .take(3):
multi_step_plot(x[0], y[0], .predict(x)[0])
#Evaluate the model on the test data
test_data_multi = tf.data.Dataset.from_tensor_slices())
test_data_mu.
Using facial recognition software in shelters for victims of domesti.pdf
Using facial recognition software in shelters for victims of domestic violence raises several
ethical concerns that must be carefully considered before pursuing such a project. Firstly, using
this technology in such a sensitive and vulnerable setting raises serious concerns about privacy,
safety, and the potential abuse of power by staff. It is essential to obtain informed consent from
guests and staff and ensure that their personal information is securely stored and not misused.
Additionally, there is a risk that this technology could be used to track and monitor guests'
movements, which could violate their rights and compromise their safety. Secondly, there is the
issue of potential bias in the technology itself, as facial recognition software has been shown to
be less accurate when identifying people of colour and women, which could result in false
accusations and wrongful identification. To address these ethical concerns, engaging in a
thorough ethical review process that involves input from diverse stakeholders, including legal
experts, privacy advocates, and survivors of domestic violence is crucial. This process should
prioritize transparency, accountability, and the protection of guests and staff's rights. Other
ethical issues that designers and developers of such an application would need to address include
the potential for hacking and data breaches, the impact on civil liberties and human rights, and
the potential for unintended consequences and harm.
Response to this article is required, please provide In-Text Citations and credible references with
the response. Thanks!.
Using a bash shell write a script using getops with options that dis.pdf
Using a bash shell write a script using getops with options that display user information based on
the users shell by searching an /etc/passwd-like file. The command will allow these options:
-a Display users with all shells. Cannot be used with -s.
-f FILE Search in FILE. FILE must be formatted like /etc/passwd.
-h Display usage information.
-s SHELL Display users with SHELL shell. SHELL must be in /etc/shells. Cannot be used with -
a..
Use the modified abstract below to answer the following two question.pdf
Use the modified abstract below to answer the following two questions:
OBJECTIVES:
The human immunodeficiency virus (HIV) and M. tuberculosis co-infection is a major global
challenge. It is not properly clear why some HIV-positive people are co-infected with
tuberculosis (TB) while others are not. This study answered this question.
METHODS:
This case-control study was conducted in Tehran, Iran, in June 2004, enrolling 2388 HIV-
positive people. Cases were selected from those who were co-infected with TB and controls from
those without TB. Multiple logistic regression analysis was performed to assess the association
between M. tuberculosis/HIV co-infection and several predictors.
RESULTS:
In this study, 241 cases were compared with 2147 controls. Sex, age, marital status, educational
level, imprisonment, smoking, narcotic addiction, route of HIV transmission, previous TB
infection, isoniazid preventive therapy (IPT), antiretroviral therapy (ART), and CD4 count were
independently associated with M. tuberculosis/HIV co-infection. However, after adjusting for all
other variables in the model, only the association between M. tuberculosis/HIV co-infection and
the following predictors were of importance: imprisoned (OR=3.82), previous TB infection
(OR=5.54).
CONCLUSIONS:
Conclusions: Several predictors are associated with M. tuberculosis/HIV co-infection, but, there
are only a few indicators that significantly affect the risk of M. tuberculosis/HIV co-infection. It
is estimated that a number of predictors of M. tuberculosis/HIV co-infection still remain
unknown and require further investigations.
Original Abstract: Molaeipoor L et al. Predictors of Tuberculosis and Human Immunodeficiency
Virus Co-infection: A Case-Control Study. Epidemiol Health. 2014 Oct 30
Flag question: Question 2
Question 2
Is there enough evidence to conclude if imprisonment or prior TB infection might have caused
co-infection with tuberculosis and HIV?
A.Yes
B. No
Question 3
What additional information would help you determine if the Odds Ratios were significantly
different form the null hypothesis (OR = 1)? Select all that apply.
Group of answer choices
A. A 95% Confidence Interval
B. The study hypothesis
C. A full list of potentially confounding variables
D. The Standard Error or Variance of the Odds Ratios
Question 4
Which of the following measures of effect are statistically significant? Select all that apply.
Group of answer choices
A. Odds Ratio = 5.0, p-value = 0.04
B. Incidence Density Ratio = 2.0, 95% CI [0.9 - 3.1]
C. Attributable Risk = 0.5, 95% CI [0.1 - 1.1]
D. Population Attributable Risk = 0.1, 95% CI = [-0.1, 0.2]
E. Cumulative Incidence Ratio = 0.5, 95% CI = [0.1 - 0.9]
F. Odds Ratio = 20, p-value = 0.2.
Use the info that os provided. I just need basic sketch I H.I. H..1..pdf
Use the info that os provided. I just need basic sketch I H.I. H..1.1.11... IHH. HHHHH1.1..
IHH.1.1.H1HHH..11 HI IHI 31 IH 11 I.1.1.1 II 1 i) 1111 IH!t!l! IIH H II 1 I If
III 11 11111 HithHI..H1...I.H1.1...11.. 11H IIIII. IHH1. .HH II HI II fif
ShImu!llumu!lluhiluIlIIIIIII fintimentintititu it.
Tory and Cathy entered into a contract under which Cathy was suppose.pdf
Tory and Cathy entered into a contract under which Cathy was supposed to provide the floral
arrangements for Torys wedding on May 23. The day of the wedding arrives, but Cathy does not
deliver the floral arrangements. Cory is devastated and feels that her wedding was ruined by the
lack of floral arrangements. She sues Cathy successfully for breach of contract and then asks for
punitive damages because her wedding was ruined. The evidence presented at court only shows
that Cathy did not deliver the arrangements because she had accidentally written the wrong
delivery date on her calendar. Answer following the IRAC method..
use Selenium to write a Java code that will Scrape data from a podca.pdf
use Selenium to write a Java code that will Scrape data from a podcast site, such as episode titles,
descriptions, and ratings. Java program should do the following: Open the website in a web
browser using Selenium. Find and interact with various elements on the page (e.g., links,
buttons, text boxes) using Selenium commands. Extract data from the page using Selenium
commands, such as finding and storing text, images, or other content. Save the scraped data in a
CSV file or other format of podcast site..
Biological Screening of Herbal Drugs in detailed.
Biological screening of herbal drugs: Introduction and Need for
Phyto-Pharmacological Screening, New Strategies for evaluating
Natural Products, In vitro evaluation techniques for Antioxidants, Antimicrobial and Anticancer drugs. In vivo evaluation techniques
for Anti-inflammatory, Antiulcer, Anticancer, Wound healing, Antidiabetic, Hepatoprotective, Cardio protective, Diuretics and
Antifertility, Toxicity studies as per OECD guidelines
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Two categories of attackers include hacktivists and state actors.
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Twitter, el popular sitio de microblogs, se ha enfrentado a graves c.pdf
Twitter, el popular sitio de microblogs, se ha enfrentado a graves cadas en el valor de sus
acciones. Esta cada en el valor de las acciones se ha producido a pesar de que la lnea superior de
la compaa creci un 74% y un 111% en los ltimos resultados trimestrales y anuales,
respectivamente. El servicio es gratuito para los usuarios, con ingresos generados principalmente
por la venta de anuncios. Por qu Twitter ha perdido el favor de los inversores? La base de
usuarios de Twitter de 302 millones de usuarios es mucho menor que la base de usuarios de
Facebook de 1.400 millones de usuarios. Instagram ha experimentado un rpido crecimiento,
acercando el tamao de su base de usuarios al de Twitter. Incluso Snapchat est ganando usuarios a
un ritmo mucho ms rpido que Twitter. La tasa de cambio est aumentando en el sentido de que
cada da se lanzan nuevas redes sociales. Por lo tanto, los inversores estn preocupados por las
presiones competitivas. En comparacin, mientras Twitter contina agregando nuevos usuarios, su
ritmo de crecimiento es lento. Esto se debe a la incapacidad de Twitter para hacer una propuesta
de valor clara a los nuevos usuarios. Aunque cientos de millones de usuarios ms se han
registrado en la plataforma de Twitter, una gran cantidad de ellos no se han convertido en
usuarios activos en la plataforma. Para combatir estos desafos, Twitter ha iniciado cambios en las
funciones de su plataforma y en su liderazgo corporativo. Twitter ha introducido nuevas
funciones para los usuarios, incluidas lneas de tiempo instantneas, pginas de inicio sin sesin y
funciones de mensajera mejoradas. Quizs an ms significativo es el cambio de liderazgo en la
parte superior de la organizacin. Jack Dorsey, cofundador y presidente de la junta, reemplazar a
Costolo como director ejecutivo, al menos hasta que se identifique un sucesor ms permanente.
La tabla enumera varias fuerzas que podran incitar a cambios en la organizacin de Twitter.
Para cada elemento, clasifique la fuerza como fuerza interna o externa.
Fuerza
Pronsticos pesimistas de los analistas de la industria
Regulaciones que afectan a la industria, como las reglas de neutralidad de la red
Innovacin que mejora la experiencia del usuario
Twitter experiment ___ cuando reemplaz a su CEO.
a. cambio de organizacion
b. innovacin
C. desarrollo organizativo
Cules de las siguientes son posibles razones por las que Twitter cambi los roles de su liderazgo
ejecutivo? Marque todo lo que corresponda.
Twitter debe lograr una mayor tasa de conversin de usuarios pasivos a activos.
Twitter se enfrenta a una mayor competencia de empresas como Facebook.
Twitter quera un proceso de toma de decisiones ms gil.
La junta directiva de Twitter exigi cambios en la estructura ejecutiva.
Cuando la junta directiva de Twitter decidi nombrar un nuevo director ejecutivo para restaurar la
confianza de los inversores, este cambio se debi principalmente a qu factor?
Una fuerza externa
Una fuerza interna
cambio organico
Mantenimiento.
Turner, Roth y Lowe son socios que comparten ingresos y p�rdidas en .pdf
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deciden liquidar la sociedad. Inmediatamente antes de la liquidacin, el balance de la sociedad
muestra activos totales, $164,400; pasivo total, $110,000; Turner, Capital, $5,700; Roth, Capital,
$15,600; y Lowe, Capital, $33,100. Los ingresos en efectivo de la venta de los activos fueron
suficientes para pagar a los acreedores todo menos $44,000. Requerido: a. Calcule la prdida por
la venta de los activos. b. Distribuya la prdida de la parte a a los socios. C. Determinar cunto, en
su caso, cada socio debe contribuir a la sociedad para cubrir cualquier deficiencia de capital
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Uber - Bir Startupn K�kenleri ve lk G�nleriDava M�terileri ele.pdf
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Dava:
Mterileri eletirmek. Ksa deien iiler. Saldrgan dzenleyiciler. Aldatc yetkililer. "Her ne pahasna
olursa olsun kazan" iyeri kltrnde kural ihlali ve acmaszln vurgulanmas. Sadece yedi ylda
balangtan 70 milyar dolarlk bir iletmeye gemek iin gereken bu mu? Yoksa bu nitelendirmeler,
kskan rakiplerin eletirileri yanl m? Uber ya da dnyann nde gelen ulam hizmetlerinden biri olan
Uber Technologies Inc. olarak bilinen dk maliyetli ara arma hizmetinin heyecanl yolculuuna
uzunca bir gz atalm.
Balarken
2008 ylnda Paris'te bir konferansa katlan teknoloji giriimcileri Garrett Camp ve Travis Kalanick,
karl bir gecede taksi bulmann zorluundan ikayet ediyorlard. Bu dei tokutan, bir dmeye
dokunarak talep zerine bir araba aracak yeni teknoloji yaratma fikri geldi. The Upstarts'ta yazar
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ortaya atan Camp, bir sredir arkada Kalanick ile akll telefon tabanl bir ehir arabas (lks araba veya
siyah araba) paylam hizmeti kavramn tartyordu.
Camp, yelerin favori web sitelerini dier insanlarla paylamalarna olanak tanyan keif ve neri
arama motoru StumbleUpon'un kurucu ortayd. Kalanick ("cal-a-nick" olarak telaffuz edilir) ilk
iini 18 yanda kurdu, bu bir SAT-hazrlk zel ders hizmetiydi. Bir dosya paylam ve hizmet ii olan
Scour, onun ikinci i macerasyd, ancak Kalanick'in byk abasna ve srarna ramen baarsz oldu. Bir
sonraki giriimi, bir video ak giriimi olan Red Swoosh'du. 2007'de 23 milyon dolara satld. Mart
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birlikte Kalanick'in "mega danman" olarak grev yapt yeni ehir arabas fikrinin denenmesinde ba
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telefon endstrisinde devrim yaratmakla kalmayp ayn zamanda genellikle "paylam ekonomisi"
olarak adlandrlan modern ibirliki ekonomiyi yaratmasyla tannan iPhone iin bir mobil
uygulamann prototipiydi.
Mart 2009'da UberCab olarak kurulan irket, mobil uygulama konseptini ilk olarak New York'ta
test etti, ardndan 2011'de San Francisco'da kullanclarn siyah lks bir araba talep etmek iin
iPhone'larnda bir dmeye basmalarna veya bir metin gndermelerine olanak tanyan bir hizmet
olarak resmi olarak lanse edildi. (limuzin), geleneksel bir taksinin fiyatnn sadece 1,5 kat.
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olarak adlandrlmasyd; bu irkette yolcular, mobil uygulama veya web sitesi araclyla hizmet talep
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ne zaman geleceini biliyorlar.
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Trilogy Enterprises Inc. de Austin, Texas, es una empresa de software de rpido crecimiento y
proporciona soluciones de software a empresas globales gigantes para mejorar las ventas y el
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prctica comercial son inusuales, pero en el entorno altamente competitivo y cambiante de
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propios horarios, a menudo muy extensos. Tienden a socializar juntos (la edad promedio es de 26
aos), tanto en la cocina bien surtida de la oficina como en eventos patrocinados por la empresa y
viajes a lugares como clubes de baile locales y retiros en Las Vegas y Hawi. Se ha desarrollado
una jerga interna y la historia compartida de la firma ha adquirido el estatus de leyenda. La
responsabilidad es pesada y llega temprano, con una actitud de "hazlo ahora" que prescinde de
largos aprendizajes. Los nuevos reclutas reciben unas pocas semanas de capacitacin intensiva,
conocida como "Universidad de Triloga" y los participantes la describen como "ms como un
campo de entrenamiento que una escuela de negocios".
La informacin se entrega como si fuera una manguera contra incendios y se espera que los
nuevos empleados comprometan su experiencia y vitalidad en todo lo que hacen. Jeff Daniel,
director de reclutamiento universitario, admite que la empresa intensa y poco convencional no es
el empleador para todos. Pero definitivamente es un entorno donde las personas apasionadas por
lo que hacen pueden prosperar. La empresa emplea a unas 700 personas tan apasionadas. Los
gerentes de Trilogy saben que el rpido crecimiento que buscan depende de tener un personal de
las mejores personas que puedan encontrar, capacitadas rpidamente y con amplia responsabilidad
y libertad lo antes posible. El CEO Joe Liemandt dice: En una empresa de software, las personas
lo son todo. No puedes construir la prxima gran empresa de software, que es lo que estamos
tratando de hacer aqu, a menos que ests totalmente comprometido con eso. Por supuesto, los
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hace que encontrar a las personas adecuadas (las llama "grandes personas") sea una misin de toda
la empresa. Los reclutadores buscan activamente a las personas ms frescas, si al menos con
experiencia, en el mercado laboral, buscando ferias de carreras universitarias y departamentos de
ciencias de la computacin para personas talentosas con ambicin e instinto empresarial.
Los altos directivos llevan a cabo las primeras rondas de entrevistas y les informan a los
prospectos que se vern presionados para lograr logros pero que sern bien recompensados. Los
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Using the packet tracer simulator, create a network topology that in.pdf
Using the packet tracer simulator, create a network topology that includes at least one router, one
switch, and several PCs.
4. Assign IP addresses and subnet masks to the devices in the network, making sure to use
appropriate IP addressing scheme.
5. Connect the devices together using the appropriate cables or connections, including
configuring VLANs on the switch.
6. Configure basic router and switch security features such as ACLs, port security, and VLAN
access controls.
7. Save the network diagram as a reference for future use.
8. Describe the process of creating a network diagram that documents the necessary data,
including IP addresses, subnet masks, and connections between devices, as well as the security
configurations implemented.
9. Submit the network diagram along with a brief report that explains the purpose and role of
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10. Analyse a sample medium complex network segment and identify common areas for
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masks to the devices in the network, making sure to use appropriate IP addressing scheme. 5.
Connect the devices together using the appropriate cables or connections, including configuring
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security, and VLAN access controls. 7. Save the network diagram as a reference for future use.
8. Describe the process of creating a network diagram that documents the necessary data,
including IP addresses, subnet masks, and connections between devices, as well as the security
configurations implemented. 9. Submit the network diagram along with a brief report that
explains the purpose and role of each device in the network, as well as the security measures
implemented and their justification 10. Analyse a sample medium complex network segment and
identify common areas for improvement and potential risks..
using silde 2 to answer silde 1 and 3 Step 17 of 40 - Create T Accou.pdf
using silde 2 to answer silde 1 and 3 Step 17 of 40 - Create T Account Listing Students
A Allowance
Step 18 of 40 - General Journal Entries
1415161718YouRTURN:Createjournalentriestorecordtheincreaseordecreaseintheatlowancebased
upontheamounteyouenteredintheTaccount..
Using financial data and information from Yahoo Finance only, calcul.pdf
Using financial data and information from Yahoo Finance only, calculate the intrinsic value (or
calculated price) of Tesla, Inc.
Using the Free Cash Flow Method of Valu.
using IRAC method Joseph was a team manager of an excursion in the O.pdf
using IRAC method Joseph was a team manager of an excursion in the Okavango Delta. Two of
Joseph' s team were attacked by elephants and left, claiming that it has become too dangerous.
With that Joseph promised the other colleague who remained, Karabo, that if she stayed and all
of the excursion work was completed, Karabo would get monies of one of the colleagues who
left without completing work. Karabo went on and agreed, but after the excursion was done, to
Karabo's surprise Joseph refuses to pay the money to Karabo. in 250-350 words ,advice Karabo
whether she is entitled to the extra payment.
Using Java programming language solve the followingSLL CLASS.pdf
Using Java programming language solve the following:
SLL CLASS:
//************************** SLL.java *********************************
// a generic singly linked list class
public class SLL {
private class SLLNode {
private T info;
private SLLNode next;
public SLLNode() {
this(null,null);
}
public SLLNode(T el) {
this(el,null);
}
public SLLNode(T el, SLLNode ptr) {
info = el; next = ptr;
}
}
protected SLLNode head, tail;
public SLL() {
head = tail = null;
}
public boolean isEmpty() {
return head == null;
}
public void addToHead(T el) {
head = new SLLNode(el,head);
if (tail == null)
tail = head;
}
public void addToTail(T el) {
if (!isEmpty()) {
tail.next = new SLLNode(el);
tail = tail.next;
}
else head = tail = new SLLNode(el);
}
public T deleteFromHead() { // delete the head and return its info;
if (isEmpty())
return null;
T el = head.info;
if (head == tail) // if only one node on the list;
head = tail = null;
else head = head.next;
return el;
}
public T deleteFromTail() { // delete the tail and return its info;
if (isEmpty())
return null;
T el = tail.info;
if (head == tail) // if only one node in the list;
head = tail = null;
else { // if more than one node in the list,
SLLNode tmp; // find the predecessor of tail;
for (tmp = head; tmp.next != tail; tmp = tmp.next);
tail = tmp; // the predecessor of tail becomes tail;
tail.next = null;
}
return el;
}
public void delete(T el) { // delete the node with an element el;
if (!isEmpty())
if (head == tail && el.equals(head.info)) // if only one
head = tail = null; // node on the list;
else if (el.equals(head.info)) // if more than one node on the list;
head = head.next; // and el is in the head node;
else { // if more than one node in the list
SLLNode pred, tmp;// and el is in a nonhead node;
for (pred = head, tmp = head.next;
tmp != null && !tmp.info.equals(el);
pred = pred.next, tmp = tmp.next);
if (tmp != null) { // if el was found;
pred.next = tmp.next;
if (tmp == tail) // if el is in the last node;
tail = pred;
}
}
}
@Override
public String toString() {
if(head == null)
return "[ ]";
String str = "[ ";
SLLNode tmp = head;
while(tmp != null){
str += tmp.info + " ";
tmp = tmp.next;
}
return str+"]";
}
public boolean contains(T el) {
if(head == null)
return false;
SLLNode tmp = head;
while(tmp != null){
if(tmp.info.equals(el))
return true;
tmp = tmp.next;
}
return false;
}
public int size(){
if(head == null)
return 0;
int count = 0;
SLLNode p = head;
while(p != null) {
count++;
p = p.next;
}
return count;
}
}
Part I: Programming Use the singly linked list class (Given below) to implement integers of
unlimited size. Each node of the list should store one digit of the integer. You are required to
implement the addition, subtraction and multiplication operations. In addition, provide a test
class that will do the following: It will keep asking the user to enter two integers, choose one of
the operations (addition, subtraction, multiplication) and then display the result. The program
will stop upon e.
using IRAC method Mary is an explorer and is about to set off on a.pdf
using IRAC method
Mary is an explorer and is about to set off on a ground-breaking expedition at the Debswana
mines. Rose and John , who are Mary's friends are also professional explorers themselves, they
then entered into a written agreement with each other that they will each help Mary from the
start to the the end of her expedition. John breaks the agreement and does not help Mary to the
end of her expedition, and instead returns home early.
in 250-350 words advise Mary as to whether she can sue John for breach of contract.
USING httpsraw.githubusercontent.comBeeDrHUIntroduction-to-Py.pdf
*USING 'https://raw.githubusercontent.com/BeeDrHU/Introduction-to-Python-CSPC-323-
/main/sales_forecast.csv'
please fix the errors for the RNN using python so the code can run without errors, Thank you*
##Defining Function to Build Multivariate Data Structure
def multivariate_data(dataset, target, start_index, end_index, history_size,
target_size, step, single_step=False):
data = []
labels = []
start_index = start_index + history_size
if end_index is None:
end_index = len(dataset) - target_size
for i in range(start_index, end_index):
indices = range(i-history_size, i, step)
data.append(dataset[indices])
if single_step:
labels.append(target[i+target_size])
else:
labels.append(target[i:i+target_size])
return np.array(data), np.array(labels)
##Define the Multi-step Plotting Structure
def multi_step_plot(history, true_future, prediction):
plt.figure(figsize=(12, 6))
num_in = create_time_steps(len(history))
num_out = len(true_future)
plt.plot(num_in, np.array(history[:, 1]), label='History')
plt.plot(np.arange(num_out)/STEP, np.array(true_future), 'bo',
label='True Future')
if prediction.any():
plt.plot(np.arange(num_out)/STEP, np.array(prediction), 'ro',
label='Predicted Future')
plt.legend(loc='upper left')
plt.show()
##Define Function to Plot training and Validation over Time
def plot_train_history(history, title):
loss = history.history['loss']
val_loss = history.history['val_loss']
epochs = range(len(loss))
plt.figure()
plt.plot(epochs, loss, 'b', label='Training loss')
plt.plot(epochs, val_loss, 'r', label='Validation loss')
plt.title(title)
plt.legend()
plt.show()
##How far into the past do you want the model to see?
past_history=
##How far into the future do you want the model to see?
future_target=
##
STEP=
df_val = len(dataset) - past_history - future_target
x_train_multi, y_train_multi = multivariate_data(dataset, dataset[:, 1], 0,
df_train, past_history,
future_target, STEP)
x_val_multi, y_val_multi = multivariate_data(dataset, dataset[:, 1],
df_train, df_val, past_history,
future_target, STEP)
##Define Constants
BATCH_SIZE =
BUFFER_SIZE =
EPOCHS =
EVALUATION_INTERVAL =
##Adding Layers Due to Complexity
train_data_multi = tf.data.Dataset.from_tensor_slices(())
train_data_multi = train_data_multi.cache().shuffle().batch().repeat()
val_data_multi = tf.data.Dataset.from_tensor_slices(())
val_data_multi = val_data_multi.batch().repeat()
multi_step_model = tf.keras.models.Sequential()
multi_step_model.add(tf.keras.layers.LSTM())
multi_step_model.add(tf.keras.layers.LSTM())
multi_step_model.add(tf.keras.layers.Dense(72))
multi_step_model.compile(optimizer=tf.keras.optimizers.RMSprop(clipvalue=1.0), loss='mae')
##Train the Model
multi_step_history = multi_step_model.fit(train_data_multi, epochs=,
steps_per_epoch=,
validation_data=,
validation_steps=50)
##Predict Future Data
for x, y in .take(3):
multi_step_plot(x[0], y[0], .predict(x)[0])
#Evaluate the model on the test data
test_data_multi = tf.data.Dataset.from_tensor_slices())
test_data_mu.
Using facial recognition software in shelters for victims of domesti.pdf
Using facial recognition software in shelters for victims of domestic violence raises several
ethical concerns that must be carefully considered before pursuing such a project. Firstly, using
this technology in such a sensitive and vulnerable setting raises serious concerns about privacy,
safety, and the potential abuse of power by staff. It is essential to obtain informed consent from
guests and staff and ensure that their personal information is securely stored and not misused.
Additionally, there is a risk that this technology could be used to track and monitor guests'
movements, which could violate their rights and compromise their safety. Secondly, there is the
issue of potential bias in the technology itself, as facial recognition software has been shown to
be less accurate when identifying people of colour and women, which could result in false
accusations and wrongful identification. To address these ethical concerns, engaging in a
thorough ethical review process that involves input from diverse stakeholders, including legal
experts, privacy advocates, and survivors of domestic violence is crucial. This process should
prioritize transparency, accountability, and the protection of guests and staff's rights. Other
ethical issues that designers and developers of such an application would need to address include
the potential for hacking and data breaches, the impact on civil liberties and human rights, and
the potential for unintended consequences and harm.
Response to this article is required, please provide In-Text Citations and credible references with
the response. Thanks!.
Using a bash shell write a script using getops with options that dis.pdf
Using a bash shell write a script using getops with options that display user information based on
the users shell by searching an /etc/passwd-like file. The command will allow these options:
-a Display users with all shells. Cannot be used with -s.
-f FILE Search in FILE. FILE must be formatted like /etc/passwd.
-h Display usage information.
-s SHELL Display users with SHELL shell. SHELL must be in /etc/shells. Cannot be used with -
a..
Use the modified abstract below to answer the following two question.pdf
Use the modified abstract below to answer the following two questions:
OBJECTIVES:
The human immunodeficiency virus (HIV) and M. tuberculosis co-infection is a major global
challenge. It is not properly clear why some HIV-positive people are co-infected with
tuberculosis (TB) while others are not. This study answered this question.
METHODS:
This case-control study was conducted in Tehran, Iran, in June 2004, enrolling 2388 HIV-
positive people. Cases were selected from those who were co-infected with TB and controls from
those without TB. Multiple logistic regression analysis was performed to assess the association
between M. tuberculosis/HIV co-infection and several predictors.
RESULTS:
In this study, 241 cases were compared with 2147 controls. Sex, age, marital status, educational
level, imprisonment, smoking, narcotic addiction, route of HIV transmission, previous TB
infection, isoniazid preventive therapy (IPT), antiretroviral therapy (ART), and CD4 count were
independently associated with M. tuberculosis/HIV co-infection. However, after adjusting for all
other variables in the model, only the association between M. tuberculosis/HIV co-infection and
the following predictors were of importance: imprisoned (OR=3.82), previous TB infection
(OR=5.54).
CONCLUSIONS:
Conclusions: Several predictors are associated with M. tuberculosis/HIV co-infection, but, there
are only a few indicators that significantly affect the risk of M. tuberculosis/HIV co-infection. It
is estimated that a number of predictors of M. tuberculosis/HIV co-infection still remain
unknown and require further investigations.
Original Abstract: Molaeipoor L et al. Predictors of Tuberculosis and Human Immunodeficiency
Virus Co-infection: A Case-Control Study. Epidemiol Health. 2014 Oct 30
Flag question: Question 2
Question 2
Is there enough evidence to conclude if imprisonment or prior TB infection might have caused
co-infection with tuberculosis and HIV?
A.Yes
B. No
Question 3
What additional information would help you determine if the Odds Ratios were significantly
different form the null hypothesis (OR = 1)? Select all that apply.
Group of answer choices
A. A 95% Confidence Interval
B. The study hypothesis
C. A full list of potentially confounding variables
D. The Standard Error or Variance of the Odds Ratios
Question 4
Which of the following measures of effect are statistically significant? Select all that apply.
Group of answer choices
A. Odds Ratio = 5.0, p-value = 0.04
B. Incidence Density Ratio = 2.0, 95% CI [0.9 - 3.1]
C. Attributable Risk = 0.5, 95% CI [0.1 - 1.1]
D. Population Attributable Risk = 0.1, 95% CI = [-0.1, 0.2]
E. Cumulative Incidence Ratio = 0.5, 95% CI = [0.1 - 0.9]
F. Odds Ratio = 20, p-value = 0.2.
Use the info that os provided. I just need basic sketch I H.I. H..1..pdf
Use the info that os provided. I just need basic sketch I H.I. H..1.1.11... IHH. HHHHH1.1..
IHH.1.1.H1HHH..11 HI IHI 31 IH 11 I.1.1.1 II 1 i) 1111 IH!t!l! IIH H II 1 I If
III 11 11111 HithHI..H1...I.H1.1...11.. 11H IIIII. IHH1. .HH II HI II fif
ShImu!llumu!lluhiluIlIIIIIII fintimentintititu it.
Tory and Cathy entered into a contract under which Cathy was suppose.pdf
Tory and Cathy entered into a contract under which Cathy was supposed to provide the floral
arrangements for Torys wedding on May 23. The day of the wedding arrives, but Cathy does not
deliver the floral arrangements. Cory is devastated and feels that her wedding was ruined by the
lack of floral arrangements. She sues Cathy successfully for breach of contract and then asks for
punitive damages because her wedding was ruined. The evidence presented at court only shows
that Cathy did not deliver the arrangements because she had accidentally written the wrong
delivery date on her calendar. Answer following the IRAC method..
use Selenium to write a Java code that will Scrape data from a podca.pdf
use Selenium to write a Java code that will Scrape data from a podcast site, such as episode titles,
descriptions, and ratings. Java program should do the following: Open the website in a web
browser using Selenium. Find and interact with various elements on the page (e.g., links,
buttons, text boxes) using Selenium commands. Extract data from the page using Selenium
commands, such as finding and storing text, images, or other content. Save the scraped data in a
CSV file or other format of podcast site..
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