Recurrence Tracking Microscope

In order to probe nanostructures on a surface we present a microscope based on the quantum recurrence phenomena. A cloud of atoms bounces off an atomic mirror connected to a cantilever and exhibits quantum recurrences. The times at which the recurrences occur depend on the initial height of the bouncing atoms above the atomic mirror, and vary following the structures on the surface under investigation. The microscope has inherent advantages over existing techniques of scanning tunneling microscope and atomic force microscope. Presently available experimental technology makes it possible to develop the device in the laboratory

On predictability of rare events leveraging social media: a machine learning perspective

Information extracted from social media streams has been leveraged to forecast the outcome of a large number of real-world events, from political elections to stock market fluctuations. An increasing amount of studies demonstrates how the analysis of social media conversations provides cheap access to the wisdom of the crowd. However, extents and contexts in which such forecasting power can be effectively leveraged are still unverified at least in a systematic way. It is also unclear how social-media-based predictions compare to those based on alternative information sources. To address these issues, here we develop a machine learning framework that leverages social media streams to automatically identify and predict the outcomes of soccer matches. We focus in particular on matches in which at least one of the possible outcomes is deemed as highly unlikely by professional bookmakers. We argue that sport events offer a systematic approach for testing the predictive power of social media, and allow to compare such power against the rigorous baselines set by external sources. Despite such strict baselines, our framework yields above 8% marginal profit when used to inform simple betting strategies. The system is based on real-time sentiment analysis and exploits data collected immediately before the games, allowing for informed bets. We discuss the rationale behind our approach, describe the learning framework, its prediction performance and the return it provides as compared to a set of betting strategies. To test our framework we use both historical Twitter data from the 2014 FIFA World Cup games, and real-time Twitter data collected by monitoring the conversations about all soccer matches of four major European tournaments (FA Premier League, Serie A, La Liga, and Bundesliga), and the 2014 UEFA Champions League, during the period between Oct. 25th 2014 and Nov. 26th 2014.Comment: 10 pages, 10 tables, 8 figure

Quantum Revivals in Periodically Driven Systems close to nonlinear resonance

We calculate the quantum revival time for a wave-packet initially well localized in a one-dimensional potential in the presence of an external periodic modulating field. The dependence of the revival time on various parameters of the driven system is shown analytically. As an example of application of our approach, we compare the analytically obtained values of the revival time for various modulation strengths with the numerically computed ones in the case of a driven gravitational cavity. We show that they are in very good agreement.Comment: 14 pages, 1 figur

Entanglement Capacity of Nonlocal Hamiltonians : A Geometric Approach

We develop a geometric approach to quantify the capability of creating entanglement for a general physical interaction acting on two qubits. We use the entanglement measure proposed by us for $N$-qubit pure states (PRA \textbf{77}, 062334 (2008)). Our procedure reproduces the earlier results (PRL \textbf{87}, 137901 (2001)). The geometric method has the distinct advantage that it gives an experimental way to monitor the process of optimizing entanglement production.Comment: 8 pages, 1 figure

Use of Oil-Based Mud Cutting Waste in Cement Clinker Manufacturing

Oil-based Mud (OBM) cutting waste is generated during the process of oil well drilling. The drilled rocks are removed from deep within the drilled well and pumped to the surface. The portion removed , known at "cutting", is a mixture of rocks, mud, water and oil. Most drilling companies store this waste in open yards with no specific treatment solution. The environmental regulations in Oman specify that storage should involve isolation, to prevent penetration of the contamination to the surface and underground water. This has made OBM waste an environmental problem, with an associated cost for oil companies. OBM chemical analysis shows an interesting compositionthat may be used in cement manufacture. It has high calcium, silicon and aluminium contents, which are the major oxides in cement manufacture. Also the oil contents are useful for reducing the fuel used during the calcining and clinkerization process. In this research, the OBM waste has been analysed and used as a constituent of the raw meal for cement clinker production. The impact of OBM addition on the resultant clinker has also been investigated

Risk Assessment and Management in Construction Industries

This paper aims to deal with construction industry risks. It deals with all type of construction industry types such as small house, malls, and huge buildings. Many accidents can be happened in the sites, so it is important that appropriate measure are taken into consideration to help in curbing the menace to improve safety in the working environment both within and the surrounding. The researchers concluded that the risks which can be avoided should be avoided to reduce the number of accidents that happen in the working environment. Rules and regulations that are clear and well understood by the workers are important in eliminating or reducing hazards experienced within the working environment. With adequate training and strict policies put in place, it is possible to deal with the risks at the workplace. The management should take responsibility and consider it as a necessity to introduce adequate measures and policies that can govern all activities undertaken in construction sites

ON DIRECT PRODUCT pure − 1 − 2 − 3 SUBGROUPS IN ABELIAN GROUP Gn×Gm

In this paper, we shall define new subgroups which are called pure−1−2−3 in abelian groups Gn×Gm for all n,m∈N which are a family of pure subgroups. In[1],[2]H.M.A.Abdullah  gave the some general properties of pure− 1−2−3 in abelian group G, but here, we shall prove more than properties on this subgroups in ModGn×Gm, which are not valid for pure subgroups

Stretching the life of Twitter classifiers with time-stamped semantic graphs

Social media has become an effective channel for communicating both trends and public opinion on current events. However the automatic topic classification of social media content pose various challenges. Topic classification is a common technique used for automatically capturing themes that emerge from social media streams. However, such techniques are sensitive to the evolution of topics when new event-dependent vocabularies start to emerge (e.g., Crimea becoming relevant to War Conflict during the Ukraine crisis in 2014). Therefore, traditional supervised classification methods which rely on labelled data could rapidly become outdated. In this paper we propose a novel transfer learning approach to address the classification task of new data when the only available labelled data belong to a previous epoch. This approach relies on the incorporation of knowledge from DBpedia graphs. Our findings show promising results in understanding how features age, and how semantic features can support the evolution of topic classifiers

Rheumatoid Arthritis Diagnosis Based on Intelligent System

التهاب المفاصل الروماتويدي  يؤثر على كثير من الناس مستهدفا المفاصل وخاصة المفاصل الصغيرة، ويستهدف جميع الأعمار حيث هو أكثر شيوعا في النساء. هذا المرض له العديد من الأعراض مشابهة لأمراض أخرى. لذلك، فمن الصعب جدا كشفه. كما أن أدوات التشخيص معقدة وغير اقتصادية. في هذا البحث، شبكة الذكاء الاصطناعي استخدمت لتشخيص والكشف المبكر عن التهاب المفاصل الروماتويدي وفقا للمعايير التي وضعتها الكلية الأمريكية للروماتيزم. أفضل أداء يحدث مع الحد الأدنى لعدد الخلايا العصبية المطلوبة عندما يكون عدد الخلايا العصبية هو 6. بحيث، فإن الأداء يساوي 10-10×3.8968. عند تقليل عدد الخلايا العصبية إلى 5 أو زيادة إلى 8، والنتيجة هي 0.0041 و  10-10×1.0611 ,على التوالي. مع ذلك، يمكن اعتبار جميع النتائج مقبولة و أن أفضل خيار لهذه التصاميم سيكون 6 خلايا عصبية من جانب التعقيد والدقة.The Rheumatoid Arthritis (RA) affects many people targeting their joints, especially small joints, and it targets all ages which it is more common in women. This disease has many symptoms similar to other diseases. Therefore, it is very hard to detect. Also, the diagnostic tools are complex and uneconomical. In this paper, artificial intelligence network used for diagnosis and early detection of RA in accordance with criteria developed by the American College of Rheumatology. The best performance occurs with the minimum number of neurons required when the number of neurons is 6. So that, the performance is equal to 3.8968x1010-.  When reducing the number of neurons to 5 or increasing to 8, the result is  0.0041 and 1.0611×10-10, respectively. However, all results can be consider acceptable and indicate that the best choice from this structure will be 6 neurons in the form of complexity and accuracy