The crime is difficult to predict; it is random and possibly can occur anywhere at any time, which is a challenging issue for any society. The study proposes a crime prediction model by analyzing and comparing three known prediction classification algorithms: Naive Bayes, Random Forest, and Gradient Boosting Decision Tree. The model analyzes the top ten crimes to make predictions about different categories, which account for 97% of the incidents. These two significant crime classes, that is, violent and nonviolent, are (...) created by merging multiple smaller classes of crimes. Exploratory data analysis is performed to identify the patterns and understand the trends of crimes using a crime dataset. The accuracies of Naive Bayes, Random Forest, and Gradient Boosting Decision Tree techniques are 65.82%, 63.43%, and 98.5%, respectively, and the proposed model is further evaluated for precision and recall matrices. The results show that the Gradient Boosting Decision Tree prediction model is better than the other two techniques for predicting crime, based on historical data from a city. The analysis and prediction model can help the security agencies utilize the resources efficiently, anticipate the crime at a specific time, and serve society well. (shrink)

To find more information on Rowman & Littlefield titles, please visit us at www.rowmanlittlefield.com.

This paper calls into question the growing tendency of quasi-absolutism within postmodern mainstream media discourse under the guise of objectivity. The tendency’s major aim is to ascribe more believability to its discourse by re-presenting that which it covers as the vehicle of objective truth to the mainstream audience. Two interweaving discourses have marked such objectivity: one in the form of indoctrinating and omnipresent narratives, which via effective propaganda become tantamount to ritualism, the other epitomised in the nostalgia for rationalisation, already (...) inherent in western positivist thought through the exponential increase of quasi-empiricism. Accordingly, what the media cover exists. What they do not remains in the order of myth. The article starts by rethinking objectivity within modern western academia, a discourse whose objectivity is already flawed from within. Then, with respect to human experience and media coverage, the paper concludes by raising the question of postmodern mainstream media’s substitution of religious quasi-absolutist narratives, be they secular or non-secular. Subjectivity thus emerges as the ultimate ground upon which our being may be legitimate. (shrink)

The detection of a human’s intended behavior is one of the most important skills that a social robot should have in order to become acceptable as a part of human society, because humans are used to understand the actions of other humans in a goal-directed manner and they will expect the social robot to behave similarly. A breakthrough in this area can advance several research branches related to social intelligence such as learning by imitation and mutual adaptation. To achieve this (...) goal the robot needs to integrate all possible evidence of intention and neglect the unintended behavior, and a complete solution should use low-level signal processing and high-level reasoning. This work explores the low-level signal processing part of the solution by proposing an interactive adaptive perception scheme that uses four important features of human behavior to amplify the signals originating from intended behavior with respect to signals originating from unintended behavior and other noise sources such as instrumental noise. This work follows the vision that intelligence is not only a function of a centralized sophisticated artificial brain, but can be presented in different forms in the entire robot including its perception and motion systems (the mind is not contained in the brain, but distributed in every cell in the body). A simple example of using the proposed scheme was implemented and the results of two experiments with it are also presented. (shrink)

Striedter's book offers precious insight into the comparative neuroanatomy of vertebrate brains, but it stops short of addressing what their evolution is all about: how effectively neural networks process information important for survival. To understand the principles of brain evolution, neuroanatomy needs to be combined not only with genetics, neurophysiology, and ethology, but also with quantitative network analyses.

Autonomous development of gaze behavior for natural human-robot interaction.

The success of social robots in achieving natural coexistence with humans depends on both their level of autonomy and their interactive abilities. Although a lot of robotic architectures have been suggested and many researchers have focused on human–robot interaction, a robotic architecture that can effectively combine interactivity and autonomy is still unavailable. This paper contributes to the research efforts toward this architecture in the following ways. First a theoretical analysis is provided that leads to the notion of co-evolution between the (...) agent and its environment and with other agents as the condition needed to combine both autonomy and interactivity. The analysis also shows that the basic competencies needed to achieve the required level of autonomy and the envisioned level of interactivity are similar but not the same. Secondly nine specific requirements are then formalized that should be achieved by the architecture. Thirdly a robotic architecture that tries to achieve those requirements by utilizing two main theoretical hypothesis and several insights from social science, developmental psychology and neuroscience is detailed. Lastly two experiments with a humanoid robot and a simulated agent are reported to show the potential of the proposed architecture. (shrink)

No one is born speaking or writing a language. We all begin as language learners, and in that sense, there are no native languages. There are only foreign languages. As language educators and as scholars of literatures produced by Black, migrant, indigenous, and multilingual artists, we know that even the universalism of “foreign languages” and “second languages”—which holds the Other at tongue’s length, so to speak—needs to be replaced by the universalism of “additional languages.” Every language is an additional language, (...) not a primary, national, or natural language. But if every language is an additional language relative to others that we use, or others that our neighbors use, it... (shrink)

With the increasing volume of data transmission through insecure communication channels, big data security has become one of the important concerns in the cybersecurity domain. To address these concerns and keep data safe, a robust privacy-preserving cryptosystem is necessary. Such a solution relies on chaos encryption algorithms over standard cryptographic methods that possess multistage encryption levels, including high speed, high security, low compute overheads, and procedural power, among other characteristics. In this work, a secure image encryption scheme is proposed using (...) linear feedback shift register and chaos-based quantum chaotic map. The focus of the scheme is mainly dependent on the secret keys from the input of the algorithm. The threat landscape, the statistical test analysis, along critical comparisons with other schemes indicate that the presented algorithm is significantly secure and is resistant to a wide range of different attacks such as differential and statistical attacks. The proposed method has sufficiently higher sensitivity and security when compared to existing encryption algorithms. Several security parameters validated the security of proposed work such as correlation coefficient analyses among the neighboring pixels, entropy, the number of pixels change rate, unified average change intensity, mean square error, brute force, key sensitivity, and peak signal to noise ratio analyses. The randomness of the ciphers produced by the proposed technique is also passed through NIST-800-22. The results of NIST indicate that the ciphers are highly random and do not produce any type of periodicity or pattern. (shrink)

Low heart rate causes a risk of death, heart disease, and cardiovascular diseases. Therefore, monitoring the heart rate is critical because of the heart’s function to discover its irregularity to detect the health problems early. Rapid technological advancement allows healthcare sectors to consolidate and analyze massive health-based data to discover risks by making more accurate predictions. Therefore, this work proposes a real-time prediction system for heart rate, which helps the medical care providers and patients avoid heart rate risk in real (...) time. The proposed system consists of two phases, namely, an offline phase and an online phase. The offline phase targets developing the model using different forecasting techniques to find the lowest root mean square error. The heart rate time-series dataset is extracted from Medical Information Mart for Intensive Care. Recurrent neural network, long short-term memory, gated recurrent units, and bidirectional long short-term memory are applied to heart rate time series. For the online phase, Apache Kafka and Apache Spark have been used to predict the heart rate in advance based on the best developed model. According to the experimental results, the GRU with three layers has recorded the best performance. Consequently, GRU with three layers has been used to predict heart rate 5 minutes in advance. (shrink)

Normal meiosis consists of a single round of DNA replication followed by two nuclear divisions. In the 1st division the chromosomes segregate reductionally whereas in the 2nd division they segregate equationally (as they do in mitosis). In certain yeast mutants, a single‐division meiosis takes place, in which some chromosomes segregate reductionally while others divide equationally. This autonomous segregation behaviour of individual chromosomes on a common spindle is determined by the centromeres they carry. The relationship between reductional segregation of a pair (...) of chromosomes and their earlier recombinational history is also discussed. (shrink)

Critical thinking continues to be viewed as a prerequisite skill for lifelong learning. It is not surprising therefore, that academic programmes delineate CT as a goal and a learning outcome. However, there are concerns regarding the extent to which the aims and objectives of the programmes are aligned with pedagogies for CT. Both the International Baccalaureate Diploma Programme and the Lebanese Baccalaureate Programme clearly delineate CT as a goal and a learning outcome. The study examines the facilitation of teaching CT (...) in the IBDP and LBP. The study was conducted in two schools located in Lebanon; one teaching the IBDP and the other the LBP. Semi structured interviews, questionnaires, and class visits were used to collect data pertaining to the teaching of CT in the two programmes in grades 11 and 12. The study is pioneering in studying the contribution of both programmes to the teaching of CT in Lebanese schools. (shrink)

Trolley dilemmas have been used to justify the intuitive appeal of the doctrine of double effect. According to this doctrine, if a good action has a harmful side effect, it is morally acceptable to do it, provided the harmful effect is not intended. However, in some variants of the dilemma, most people are willing to forego this doctrine, thus making responses inconsistent. In this study, 404 university students from the United Arab Emirates (UAE) were presented with 4 versions of the (...) trolley dilemma. Results came out showing that higher levels of depressive symptoms predict greater consistency in adherence (or rejection) to the doctrine of double effect. Likewise, higher levels of depressive symptom predict utilitarian responses to trolley dilemmas. Anxiety symptoms had similar effects, but more moderate. Demographic variables (age, gender) were also assessed as predictors of responses and consistency to trolley scenarios, but no significant effects were found. (shrink)

The purpose of this study was to examine the relationship between metacognition as measured in real-life situations and IQ scores as reflected by performance on the Raven Standard Progressive Matrices Scale. It is also intended in this study to report on whether or not there were significant differences in performance on the metacognitive instrument among participants with typical development, deaf and hard-of-hearing, and low-achieving individuals with and without the influence of IQ. Analysis showed significant correlations between IQ, metacognitive test, and (...) metacognitive test scores divided by mean reaction time but not with reaction time itself. Results revealed the influence of IQ on metacognition being greater than the influence of metacognition on IQ. Results showed when controlling for the effect of IQ, differences among the three groups of participants on the metacognitive instrument become non-significant. Implications and suggestions are presented. (shrink)

The article studies the impact of Fintech on entrepreneurship in Arabic region by using Crowdfunding platforms as the field of study. The article focuses on Arabic Crowdfunding platforms. The population of (12) platforms consist of: individuals, entrepreneurs, investors, employees at Crowdfunding platforms. Descriptive and quantitative approach used in this article, and a questionnaire used as a tool to collect primary data. The results indicate an impact for Fintech on entrepreneurship in general and obvious obstacles to use it widely in Arabic (...) region cause of legislations or e-payments. The article recommended more awareness for innovative products and services such as Fintech, Crowdfunding and adopting the culture of e-business models. Also the article promoting the process of developing regulations that organize e-business models, especially Fintech and Crowdfunding, the use of modern communication technology to serve the development of society, more interest to innovation and creativity as a key factor for entrepreneurial success. (shrink)

The increasing global demand for energy necessitates devoted attention to the formulation and exploration of mechanisms of thermal heat exchangers to explore and save heat energy. Thus, innovative thermal transport fluids require to boost thermal conductivity and heat flow features to upsurge convection heat rate, and nanofluids have been effectively employed as standard heat transfer fluids. With such intention, herein, we formulated and developed the constitutive flow laws by utilizing the Rossland diffusion approximation and Stephen’s law along with the MHD (...) effect. The mathematical formulation is based on boundary layer theory pioneered by Prandtl. Governing nonlinear partial differential flow equations are changed to ODEs via the implementation of the similarity variables. A well-known computational algorithm BVPh2 has been utilized for the solution of the nonlinear system of ODEs. The consequence of innumerable physical parameters on flow field, thermal distribution, and solutal field, such as magnetic field, Lewis number, velocity parameter, Prandtl number, drag force, Nusselt number, and Sherwood number, is plotted via graphs. Finally, numerical consequences are compared with the homotopic solution as a limiting case, and an exceptional agreement is found. (shrink)

Nowadays, online product reviews have been at the heart of the product assessment process for a company and its customers. They give feedback to a company on improving product quality, planning, and monitoring its business schemes in order to increase sale and gain more profit. They are also helpful for customers to select the right products in less effort and time. Most companies make spam reviews of products in order to increase the products sales and gain more profit. Detecting spam (...) product reviews is a challenging issue in NLP. Numerous machine learning approaches have attempted to detect and classify the product reviews as spam or nonspam. However, in order to improve the classification accuracy, this study has introduced an ensemble machine learning model that combines predictions from multilayer perceptron, K-Nearest Neighbour, and Random Forest and predicts the outcome of the review as spam or real, based on the majority vote of the contributing models. In order to accomplish the task of spam review classification, the proposed ensemble and other benchmark boosting approaches are tested with 25 statistical features extracted from mobile application reviews of Yelp Dataset. Then, three different selection techniques are exploited to diminish the feature space and filter out the top 10 optimal features. The effectiveness of the proposed ensemble, the individual models, and other benchmark boosting approaches is again evaluated with 10 optimal features in terms of classification accuracy. Experimental outcomes illustrate that the proposed ensemble model outperformed the individual classifiers and state-of-the-art boosting approaches like Generalized Boost Regression Model, Extreme Gradient Boost, and AdaBoost Regression Model in terms of classification accuracy. (shrink)

Autism Spectrum Disorder (ASD) is extremely heterogeneous clinically and genetically. There is a pressing need for a better understanding of the heterogeneity of ASD based on scientifically rigorous approaches centered on systematic evaluation of the clinical and research utility of both phenotype and genotype markers. This paper presents a holistic PheWAS-inspired method to identify meaningful associations between ASD phenotypes and genotypes. We generate two types of phenotype-phenotype (p-p) graphs: a direct graph that utilizes only phenotype data, and an indirect graph (...) that incorporates genotype as well as phenotype data. We introduce a novel methodology for fusing the direct and indirect p-p networks in which the genotype data is incorporated into the phenotype data in varying degrees. The hypothesis is that the heterogeneity of ASD can be distinguished by clustering the p-p graph. The obtained graphs are clustered using network-oriented clustering techniques, and results are evaluated. The most promising clusterings are subsequently analyzed for biological and domain-based relevance. Clusters obtained delineated different aspects of ASD, including differentiating ASD-specific symptoms, cognitive, adaptive, language and communication functions, and behavioral problems. Some of the important genes associated with the clusters have previous known associations to ASD. We found that clusters based on integrated genetic and phenotype data were more effective at identifying relevant genes than clusters constructed from phenotype information alone. These genes included five with suggestive evidence of ASD association and one known to be a strong candidate. (shrink)

The extended neoteric ranked set sampling plan proposed by Taconeli and Cabral has proven to outperform many one stages and two stages ranked set sampling plans when estimating the mean and the variance for different populations. Therefore, in this paper, the likelihood function based on ENRSS is proposed and used for estimation of the parameters of the inverted Nadarajah–Haghighi distribution. An extensive Monte Carlo simulation study is conducted to assess the performance of the proposed likelihood function, and the efficiency of (...) the estimated parameters based on ENRSS is compared with the well-known ranked set sampling plan and some of its modifications. These modifications include the extended ranked set sampling plan and the neoteric ranked set sampling plan. The results as foreseeable were very satisfactory and gave similar results to Taconeli and Cabral’s 2019 results. (shrink)

Virtual screening is the most critical process in drug discovery, and it relies on machine learning to facilitate the screening process. It enables the discovery of molecules that bind to a specific protein to form a drug. Despite its benefits, virtual screening generates enormous data and suffers from drawbacks such as high dimensions and imbalance. This paper tackles data imbalance and aims to improve virtual screening accuracy, especially for a minority dataset. For a dataset identified without considering the data’s imbalanced (...) nature, most classification methods tend to have high predictive accuracy for the majority category. However, the accuracy was significantly poor for the minority category. The paper proposes a K-mean algorithm coupled with Synthetic Minority Oversampling Technique to overcome the problem of imbalanced datasets. The proposed algorithm is named as KSMOTE. Using KSMOTE, minority data can be identified at high accuracy and can be detected at high precision. A large set of experiments were implemented on Apache Spark using numeric PaDEL and fingerprint descriptors. The proposed solution was compared to both no-sampling method and SMOTE on the same datasets. Experimental results showed that the proposed solution outperformed other methods. (shrink)

Online forums have become the main source of knowledge over the Internet as data are constantly flooded into them. In most cases, a question in a web forum receives several responses, making it impossible for the question poster to obtain the most suitable answer. Thus, an important problem is how to automatically extract the most appropriate and high-quality answers in a thread. Prior studies have used different combinations of both lexical and nonlexical features to retrieve the most relevant answers from (...) discussion forums, and hence, there is no standard/general set of features that could be effectively used for relevant answer/reply post classification. However, this study proposed an answer detection model that is exclusively relying on lexical features and employs a random forest classifier for classification of answers in discussion boards. Experimental results showed that the proposed answer detection model outperformed the baseline technique and other state-of-the-art machine learning algorithms in terms of classification accuracy on benchmark forum datasets. (shrink)

“Neutrosophics Knowledge” has been created for publications on advanced studies in neutrosophy, neutrosophic set, neutrosophic logic, neutrosophic probability, neutrosophic statistics that started in 1995 and their applications in any field, such as the neutrosophic structures developed in algebra, geometry, topology, etc. The submitted papers should be professional, in good English and Arabic, containing a brief review of a problem and obtained results. Neutrosophy is a new branch of philosophy that studies the origin, nature, and scope of neutralities, as well as (...) their interactions with different ideational spectra. (shrink)

The coronavirus outbreak around the world has caused public health concerns and changes in peoples’ behaviors and psychological distress. The pandemic impacts on human behavior, emotions, and cognition, leading to diverse reactions in relation to awareness of the disease. However, there is little understanding around the psychological impacts of the pandemic and strategies to overcome this impact. This study aimed to examine individuals’ reactions toward the COVID-19 pandemic in relation to their psychological hardiness, their degree of awareness toward the pandemic, (...) and precautionary measures taken. Individuals living in Saudi Arabia were invited to complete an online questionnaire which included demographic items, psychological responses to the pandemic, awareness of COVID-19, and measures of psychological hardiness. A total of 1272 individuals were recruited into the study, with the majority being female. Results indicated that the average psychological responses to the COVID-19 pandemic in the study sample were 75.85%. This indicates that the sample generally has a high level of positive psychological responses to the COVID-19 pandemic. The awareness of COVID-19 among Saudi was 91.50%. This indicates a high level of awareness among the study sample. (shrink)

This paper introduces the new novel four-parameter Weibull distribution named as the Marshall–Olkin alpha power Weibull distribution. Some statistical properties of the distribution are examined. Based on Type-I censored and Type-II censored samples, maximum likelihood estimation, maximum product spacing, and Bayesian estimation for the MOAPW distribution parameters are discussed. Numerical analysis using real data sets and Monte Carlo simulation are accomplished to compare various estimation methods. This novel model’s supremacy upon some famous distributions is explained using two real data sets (...) and it is shown that the MOAPW model can achieve better fits than other competitive distributions. (shrink)

Introduction: Cognitive behavioral therapy for children and adolescents has shown efficacy in treating different psychiatric disorders. It has been added to multiple clinical guidelines as the first-line treatment. However, despite more studies of its efficacy, CBT is underutilized in clinical settings due to a lack of rigorous training programs and qualified CBT therapists. The limited knowledge of parents in this intervention and their negative attitudes toward it have been considered as possible reasons.Methods: This is a cross-sectional survey-based study among 464 (...) Saudi parents living in Riyadh city. We aimed to evaluate the preference, knowledge, and attitudes of Saudi parents toward CBT for their children. We compared the difference in the level of knowledge and attitudes toward CBT in relation to the characteristics of parents. An online questionnaire that included 39 questions was carefully reconstructed from four validated scales, approved by an expert panel, and piloted. Participants were recruited to participate through online social media.Results: Saudi parents had average knowledge about CBT; however, they had positive attitudes toward the therapy itself and its role in treating the behavioral issues of children. Male participants showed better knowledge than female participants. Participants with higher education and those with high income had more favorable attitudes toward CBT than others.Conclusion: The knowledge of parents is considered inadequate and indicated the need for more awareness and perhaps mass education. In contrast, they maintained positive attitudes and were interested in evidence-based treatment, with more preference toward non-psychopharmacological interventions. (shrink)

This article attempts to study cost minimizing multi-objective fractional solid transportation problem with fuzzy cost coefficients c ˜ i j k r {\tilde{c}}_{ijk}^{r}, fuzzy supply quantities a ˜ i {\tilde{a}}_{i}, fuzzy demands b ˜ j {\tilde{b}}_{j}, and/or fuzzy conveyances e ˜ k {\tilde{e}}_{k}. The fuzzy efficient concept is introduced in which the crisp efficient solution is extended. A necessary and sufficient condition for the solution is established. Fuzzy geometric programming approach is applied to solve the crisp problem by defining membership (...) function so as to obtain the optimal compromise solution of a multi-objective two-stage problem. A linear membership function for the objective function is defined. The stability set of the first kind is defined and determined. A numerical example is given for illustration and to check the validity of the proposed approach. (shrink)

This paper is concerned with the estimation of the Weibull generalized exponential distribution parameters based on the adaptive Type-II progressive censored sample. Maximum likelihood estimation, maximum product spacing, and Bayesian estimation based on Markov chain Monte Carlo methods have been determined to find the best estimation method. The Monte Carlo simulation is used to compare the three methods of estimation based on the ATIIP-censored sample, and also, we made a bootstrap confidence interval estimation. We will analyze data related to the (...) distribution about single carbon fiber and electrical data as real data cases to show how the schemes work in practice. (shrink)

This sixth volume of Collected Papers includes 74 papers comprising 974 pages on (theoretic and applied) neutrosophics, written between 2015-2021 by the author alone or in collaboration with the following 121 co-authors from 19 countries: Mohamed Abdel-Basset, Abdel Nasser H. Zaied, Abduallah Gamal, Amir Abdullah, Firoz Ahmad, Nadeem Ahmad, Ahmad Yusuf Adhami, Ahmed Aboelfetouh, Ahmed Mostafa Khalil, Shariful Alam, W. Alharbi, Ali Hassan, Mumtaz Ali, Amira S. Ashour, Asmaa Atef, Assia Bakali, Ayoub Bahnasse, A. A. Azzam, Willem K.M. Brauers, (...) Bui Cong Cuong, Fausto Cavallaro, Ahmet Çevik, Robby I. Chandra, Kalaivani Chandran, Victor Chang, Chang Su Kim, Jyotir Moy Chatterjee, Victor Christianto, Chunxin Bo, Mihaela Colhon, Shyamal Dalapati, Arindam Dey, Dunqian Cao, Fahad Alsharari, Faruk Karaaslan, Aleksandra Fedajev, Daniela Gîfu, Hina Gulzar, Haitham A. El-Ghareeb, Masooma Raza Hashmi, Hewayda El-Ghawalby, Hoang Viet Long, Le Hoang Son, F. Nirmala Irudayam, Branislav Ivanov, S. Jafari, Jeong Gon Lee, Milena Jevtić, Sudan Jha, Junhui Kim, Ilanthenral Kandasamy, W.B. Vasantha Kandasamy, Darjan Karabašević, Songül Karabatak, Abdullah Kargın, M. Karthika, Ieva Meidute-Kavaliauskiene, Madad Khan, Majid Khan, Manju Khari, Kifayat Ullah, K. Kishore, Kul Hur, Santanu Kumar Patro, Prem Kumar Singh, Raghvendra Kumar, Tapan Kumar Roy, Malayalan Lathamaheswari, Luu Quoc Dat, T. Madhumathi, Tahir Mahmood, Mladjan Maksimovic, Gunasekaran Manogaran, Nivetha Martin, M. Kasi Mayan, Mai Mohamed, Mohamed Talea, Muhammad Akram, Muhammad Gulistan, Raja Muhammad Hashim, Muhammad Riaz, Muhammad Saeed, Rana Muhammad Zulqarnain, Nada A. Nabeeh, Deivanayagampillai Nagarajan, Xenia Negrea, Nguyen Xuan Thao, Jagan M. Obbineni, Angelo de Oliveira, M. Parimala, Gabrijela Popovic, Ishaani Priyadarshini, Yaser Saber, Mehmet Șahin, Said Broumi, A. A. Salama, M. Saleh, Ganeshsree Selvachandran, Dönüș Șengür, Shio Gai Quek, Songtao Shao, Dragiša Stanujkić, Surapati Pramanik, Swathi Sundari Sundaramoorthy, Mirela Teodorescu, Selçuk Topal, Muhammed Turhan, Alptekin Ulutaș, Luige Vlădăreanu, Victor Vlădăreanu, Ştefan Vlăduţescu, Dan Valeriu Voinea, Volkan Duran, Navneet Yadav, Yanhui Guo, Naveed Yaqoob, Yongquan Zhou, Young Bae Jun, Xiaohong Zhang, Xiao Long Xin, Edmundas Kazimieras Zavadskas. (shrink)

In September President Bush reasserted his commitment to the "road map" for Middle East peace, launched in 2003 to achieve a comprehensive Israeli-Palestinian agreement by 2005. He called on Palestinians to renounce terrorism, implicitly urged world leaders to cut ties to Yasser Arafat, and appealed to Israel to end "the daily humiliation" of Palestinians. He framed his remarks within an overall appeal for democracy in the Arab world, citing Iraq as a model of the "transformational power of liberty." In (...) fact, for more than a year the US disastrously ignored Ayatollah Ali al-Sistani's pleas to set up elections. Real democracy is the willingness to accept results we may not like. US policy on a future Palestinian state is just as short-sighted. (shrink)