Intelligent personal assistants (IPAs) such as Amazon Alexa, Google Assistant and Apple Siri extend their built-in capabilities by supporting voice apps developed by third-party developers. Sometimes the smart assistant is not able to successfully re
spond to user voice commands (aka utterances). There are many reasons including automatic speech recognition (ASR) error, natural language understanding (NLU) error, routing utterances to an irrelevant voice app or simply that the user is asking for a capability that is not supported yet. The failure to handle a voice command leads to customer frustration. In this paper, we introduce a fallback skill recommendation system to suggest a voice app to a customer for an unhandled voice command. One of the prominent challenges of developing a skill recommender system for IPAs is partial observation. To solve the partial observation problem, we propose collaborative data relabeling (CDR) method. In addition, CDR also improves the diversity of the recommended skills. We evaluate the proposed method both offline and online. The offline evaluation results show that the proposed system outperforms the baselines. The online A/B testing results show significant gain of customer experience metrics.
In this paper, we introduce FITAnnotator, a generic web-based tool for efficient text annotation. Benefiting from the fully modular architecture design, FITAnnotator provides a systematic solution for the annotation of a variety of natural language p
rocessing tasks, including classification, sequence tagging and semantic role annotation, regardless of the language. Three kinds of interfaces are developed to annotate instances, evaluate annotation quality and manage the annotation task for annotators, reviewers and managers, respectively. FITAnnotator also gives intelligent annotations by introducing task-specific assistant to support and guide the annotators based on active learning and incremental learning strategies. This assistant is able to effectively update from the annotator feedbacks and easily handle the incremental labeling scenarios.
In this paper, it has
merged two techniques of the artificial intelligent, they are the
ants colony optimization algorithm and the genetic algorithm, to
The recurrent reinforcement learning trading system
optimization. The proposed trading system
is based on an ant
colony optimization algorithm and the genetic algorithm to
select an optimal group of technical indicators, and fundamental
indicators.
The study main to know the effect of the program ' Right Intelligent System
Knowledge 'on the development of the critical thinking for Students Faculty of
Agriculture in University of Teashreen. The sample of the research was chosen
intentionally
, it composed of (72) students. The study had the quasi-experimental
methodology in terms of dividing the research sample into two groups: the experimental
group which consisted of (36) students, and the control group which consisted of (36)
students. The researcher used "Right Intelligent System of Knowledge " Program: It is
translated by Dr. Nadia Al-sourour in (2005), which taught the students how to think. The
program consisted of four parts: Living Skills, The System, The Power of Thinking, and
Success. It is suitable for students from the fifth grade till university level. And researcher
used California's Test for critical thinking: is translated by each of Abdullal Ague and Adel
Albanna, and it was adopted by the current study Photo-verbal of this test, for measuring
the capacity: the total score, analysis, evaluation, inference. The study showed that: there
was a statistically significant difference between experimental and control groups
according to California's Test for critical thinking including with the dimensions of
analysis, evaluation, inference, and the total degree as a result of the post, so this difference
is due to the right intelligent system of knowledge program, and this shows the
effectiveness of this program and its ability to develop critical thinking skills. Too, there
was no statistically significant difference between male and female students from the
experimental group on the California's Test of critical thinking including with the
dimensions of analysis, evaluation, inference, and the total degree.
The research aims through his studies to determine the effectiveness of the
administrative factors in the application of multi-modal transport system. He also aims to
determine the effectiveness of logistical factors in the application of this syst
em, and assess
the extent of the efficiency of the nessessary infrastructure for the application of this
system. The researcher adobted to test his hypotheses on the preliminary data obtained
through a distribution of a questionnaire to the workers of the container terminal of the
Port of Latakia, the customs agents and shipping companies, and the number of the
respondents was about 60 people. The researcher used the "Student" test sample as one
sample in order to test his hypotheses. He conducted demographic descriptions for the
members of the sample,Cronbach's alpha coefficient to measure the stability was 0,911.
The study concluded: Poor logistic service in the container terminal at the Port of
Latakia and the weakness of qualified and trained staff to use the method of transport.
The researcher found at the end of the study: The need to update all the infrastructure
related to each place and take advantage of the geographical location of Syria.
This paper presents a method for finding online adaptive optimal
controllers for continuous-time linear systems without knowing the
system dynamical matrices. The proposed method employs one of
Intelligent Operations Research Techniques, this tech
nique is the
adaptive dynamic programming, to iteratively solve the algebraic
Riccati equation using the online information of state and input,
without requiring the a priori knowledge of the system dynamics. In
addition, all iterations can be conducted by using repeatedly the
same state and input information on some fixed time intervals. A
practical online algorithm is developed in this paper, and is applied
to the controller design for a turbocharged diesel engine with
exhaust gas recirculation.
The typical and comfortable lighting is the one that responds to the
requirements of both health and economy. The more architecture is
able to achieve good lighting that provides adequate conditions for
living and practicing various activities, the better productivity is.
Traffic jam is a serious problem in our life, it causes waste of time and energy, conventional traffic light control system works with a fixed time and fixed cycle. This paper proposes an intelligent traffic light control system with a changeable gre
en time and cycle depending on traffic density. Traffic parameters (cars’ numbers, density, flow) are collected by Loop Detectors located at each traffic signal, this data will be transmitted to the PLC controller then, PLC processes this data to produce controlling commands, it is also connected to a SCADA system which supervises the process and provides an automatic and manual control.
The proposal system applies Green Wave method to connect between two junctions based on a real car velocity and sets priority for emergency car, when Loop Detector detects this car the program will be interrupted to open the traffic light needed.
This intelligent system is experimented with conventional control system s’ data the obtained result is promising, it can reduce the green time, cycle time, and delayed time of each car at traffic light to its’ minimum value.
Assessing the reality of economic institutions in developing countries shows lack of awareness of the concepts of intellectual capital and dimensions of knowledge that exist to achieve a competitive advantage in a global economy. Competitive advantag
e requires knowledge of how to manage intellectual capital and turn it into an additional value. This in turn requires companies to search for creative ideas and intellectual skills in order to achieve their strategic objectives in view of intense competition globally. This research tries to assess the role of investment in intellectual capital in helping the Syrian Communication company secure a competitive advantage.
This research traces, after conducting a wide literature survey, the areas not covered by prominent agent oriented software engineering (AOSE) methodologies. Each methodology has its strength and weakness and focuses on some stages of software
devel
opment lifecycle but not all stages. This paper presents an addition to a well established AOSE methodology (MaSE). MaSE is considered one of the strongest in the field, it does not, however, support handling early requirements. This work integrates MaSE with another methodology known for its strength in early requirement representation. The integration implied the development of a wide set of translation rules between two different environments of notations and graphical representations. A software tool was developed to automate the translation and a case study is used to demonstrate the work.
