Palestine Smart Tourism Augmented Reality Mobile Application

Tourism is considered an important sector for most countries, while maintaining good tourism attractions can promote national economic development. The State of Palestine is historically considered a wealthy country full of many archaeological places. In the city of Bethlehem, for example, the Church of the Nativity is the most important touristic site, but it does not have enough technology development to attract tourists. In this paper, we propose a smart mobile application named “Pal-STAR” (Palestine Smart Tourist Augmented Reality) as an innovative solution which targets tourists and assists them to make a visit inside the Church of the Nativity. The application will use augmented reality and feature a virtual tourist guide showing views of the church while providing historical information in a smart, easy, effective and user-friendly way. The proposed application is compatible with multiple mobile platforms and is considered user friendly. The findings show that this application will improve the practice of the tourism sector in the Holy Land, it will also increase the number of tourists visiting the Church of the Nativity and it will facilitate access to historical data that have been difficult to obtain using traditional tourism guidance. The value that tourism adds to a country cannot be denied, and the more technological advances are incorporated in this sector, the better the country’s tourism sector can be served. Palestine’s economy is heavily dependent on tourism in many of its main cities, despite several limitations, and technological development is needed to enable this sector to flourish. The proposed mobile application would definitely have a good impact on the development of the tourism sector by creating an Augmented Reality environment for tourists inside the church, helping them to navigate and learn about holy places in a non-traditional way, using a virtual tourist guide.

Reduction of Energy Consumption Using Smart Home Techniques in the Household Sector

Outcomes of exhaustion of natural resources started influencing each spirit on this planet. Energy is an essential factor in this aspect. To restore the circumstance to the appropriate track, all attempts must focus on two fundamental branches: producing electricity from clean and renewable reserves and decreasing the overall unnecessary consumption of energy. The focal point of this paper will be on lessening the power consumption in the household's segment. This paper is an attempt to give a clear understanding of a framework called Reduction of Energy Consumption in Household Sector (RECHS) and how it should help householders to reduce their power consumption by substituting their household appliances, turning-off the appliances when stand-by modus is detected, and scheduling their appliances operation periods. Technically, the framework depends on utilizing Z-Wave compatible plug-ins which will be connected to the usual house devices to gauge and control them remotely and semi-automatically. The suggested framework underpins numerous quality characteristics, for example, integrability, scalability, security and adaptability.

A Machine Learning Based Framework for Education Levelling in Multicultural Countries: UAE as a Case Study

In Abu Dhabi, there are many different education curriculums where sector of private schools and quality assurance is supervising many private schools in Abu Dhabi for many nationalities. As there are many different education curriculums in Abu Dhabi to meet expats’ needs, there are different requirements for registration and success. In addition, there are different age groups for starting education in each curriculum. In fact, each curriculum has a different number of years, assessment techniques, reassessment rules, and exam boards. Currently, students that transfer curriculums are not being placed in the right year group due to different start and end dates of each academic year and their date of birth for each year group is different for each curriculum and as a result, we find students that are either younger or older for that year group which therefore creates gaps in their learning and performance. In addition, there is not a way of storing student data throughout their academic journey so that schools can track the student learning process. In this paper, we propose to develop a computational framework applicable in multicultural countries such as UAE in which multi-education systems are implemented. The ultimate goal is to use cloud and fog computing technology integrated with Artificial Intelligence techniques of Machine Learning to aid in a smooth transition when assigning students to their year groups, and provide leveling and differentiation information of students who relocate from a particular education curriculum to another, whilst also having the ability to store and access student data from anywhere throughout their academic journey.

A Tribe, a County, and a Casino: Socioeconomic Disparities between the Mohegan Tribe and New London County through Two Decades

Since British established colonial settlements across the East Coast, Native Americans have suffered stark socio economic disparities in comparison to their neighboring communities. This paper employs the 1990, 2000, and 2010 United States Decennial Census to assess whether and to what extent the casino economy helped to close this socioeconomic gap between the Mohegan tribe and its surrounding community. These three Decennial Censuses cover two decades, from six years prior to the erection of Mohegan Sun casino to 14 years afterwards, including the Great Recession 2007-2009. Income, employment, education and housing parameters are selected as socio economic indicators. The profitable advent of the Mohegan Sun in 1996 dramatically improved the socio economic status of the Mohegan Tribe between 1990 and 2000. In fact, for most of these indicators––poverty, median household income, employment, home ownership, and car ownership––disparities shifted; tribal socioeconomic parameters improved from well below the level of New London County in 1990, to the same level or above the county rates in 2000. However, economic downturn in 2007-2009 Great Recession impacted Mohegan people remarkably. By 2010, disparities for household income, employment, home ownership, and car ownership returned. The casino bridged socio economic inequalities, but at the face of economic crises, the mono-product economy grew vulnerable.

A Particle Swarm Optimal Control Method for DC Motor by Considering Energy Consumption

In the actual start-up process of DC motors, the DC drive system often faces a conflict between energy consumption and acceleration performance. To resolve the conflict, this paper proposes a comprehensive performance index that energy consumption index is added on the basis of classical control performance index in the DC motor starting process. Taking the comprehensive performance index as the cost function, particle swarm optimization algorithm is designed to optimize the comprehensive performance. Then it conducts simulations on the optimization of the comprehensive performance of the DC motor on condition that the weight coefficient of the energy consumption index should be properly designed. The simulation results show that as the weight of energy consumption increased, the energy efficiency was significantly improved at the expense of a slight sacrifice of fastness indicators with the comprehensive performance index method. The energy efficiency was increased from 63.18% to 68.48% and the response time reduced from 0.2875s to 0.1736s simultaneously compared with traditional proportion integrals differential controller in energy saving.

Research on Morning Commuting Behavior under Autonomous Vehicle Environment Based on Activity Method

Based on activity method, this paper focuses on morning commuting behavior when commuters travel with autonomous vehicles (AVs). Firstly, a net utility function of commuters is constructed by the activity utility of commuters at home, in car and at workplace, and the disutility of travel time cost and that of schedule delay cost. Then, this net utility function is applied to build an equilibrium model. Finally, under the assumption of constant marginal activity utility, the properties of equilibrium are analyzed. The results show that, in autonomous driving, the starting and ending time of morning peak and the number of commuters who arrive early and late at workplace are the same as those in manual driving. In automatic driving, however, the departure rate of arriving early at workplace is higher than that of manual driving, while the departure rate of arriving late is just the opposite. In addition, compared with manual driving, the departure time of arriving at workplace on time is earlier and the number of people queuing at the bottleneck is larger in automatic driving. However, the net utility of commuters and the total net utility of system in automatic driving are greater than those in manual driving.

Model of Obstacle Avoidance on Hard Disk Drive Manufacturing with Distance Constraint

Obstacle avoidance is the one key for the robot system in unknown environment. The robots should be able to know their position and safety region. This research starts on the path planning which are SLAM and AMCL in ROS system. In addition, the best parameters of the obstacle avoidance function are required. In situation on Hard Disk Drive Manufacturing, the distance between robots and obstacles are very serious due to the manufacturing constraint. The simulations are accomplished by the SLAM and AMCL with adaptive velocity and safety region calculation.

Fast Approximate Bayesian Contextual Cold Start Learning (FAB-COST)

Cold-start is a notoriously difficult problem which can occur in recommendation systems, and arises when there is insufficient information to draw inferences for users or items. To address this challenge, a contextual bandit algorithm – the Fast Approximate Bayesian Contextual Cold Start Learning algorithm (FAB-COST) – is proposed, which is designed to provide improved accuracy compared to the traditionally used Laplace approximation in the logistic contextual bandit, while controlling both algorithmic complexity and computational cost. To this end, FAB-COST uses a combination of two moment projection variational methods: Expectation Propagation (EP), which performs well at the cold start, but becomes slow as the amount of data increases; and Assumed Density Filtering (ADF), which has slower growth of computational cost with data size but requires more data to obtain an acceptable level of accuracy. By switching from EP to ADF when the dataset becomes large, it is able to exploit their complementary strengths. The empirical justification for FAB-COST is presented, and systematically compared to other approaches on simulated data. In a benchmark against the Laplace approximation on real data consisting of over 670, 000 impressions from autotrader.co.uk, FAB-COST demonstrates at one point increase of over 16% in user clicks. On the basis of these results, it is argued that FAB-COST is likely to be an attractive approach to cold-start recommendation systems in a variety of contexts.

Integrated Modeling of Transformation of Electricity and Transportation Sectors: A Case Study of Australia

The proposed stringent mitigation targets require an immediate start for a drastic transformation of the whole energy system. The current Australian energy system is mainly centralized and fossil fuel-based in most states with coal and gas-fired plants dominating the total produced electricity over the recent past. On the other hand, the country is characterized by a huge, untapped renewable potential, where wind and solar energy could play a key role in the decarbonization of the Australia’s future energy system. However, integrating high shares of such variable renewable energy sources (VRES) challenges the power system considerably due to their temporal fluctuations and geographical dispersion. This raises the concerns about flexibility gap in the system to ensure the security of supply with increasing shares of such intermittent sources. One main flexibility dimension to facilitate system integration of high shares of VRES is to increase the cross-sectoral integration through coupling of electricity to other energy sectors alongside the decarbonization of the power sector and reinforcement of the transmission grid. This paper applies a multi-sectoral energy system optimization model for Australia. We investigate the cost-optimal configuration of a renewable-based Australian energy system and its transformation pathway in line with the ambitious range of proposed climate change mitigation targets. We particularly analyse the implications of linking the electricity and transport sectors in a prospective, highly renewable Australian energy system.

Awareness Level of Green Computing among Computer Users in Kebbi State, Nigeria

This study investigated the awareness level of green computing possessed by computer users in Kebbi state. Survey method was employed to carry out the study. The study involved computer users from ICT business/training centers around Argungu and Birnin Kebbi areas of Kebbi state. Purposive sampling method was used to draw 156 respondents that volunteer to answer the questionnaire administered for gathering the data of the study. Out of the 156 questionnaires distributed, 121 were used for data analysis. In all, 79 respondents were from Argungu, while 42 were from Birnin Kebbi. The two research questions of the study were answered with descriptive statistic (percentage), and inferential statistics (ANOVA). The findings showed that the most of the computer users do not possess adequate awareness on conscious use of computing system. Also, the study showed that there is no significant difference regarding the consciousness of green computing possesses among computer users in Argungu and Birnin Kebbi. Based on these findings, the study suggested among others an aggressive campaign on green computing practice among computer users in Kebbi state.

The OLOS® Way to Cultural Heritage: User Interface with Anthropomorphic Characteristics

Augmented Reality and Augmented Intelligence are radically changing information technology. The path that starts from the keyboard and then, passing through milestones such as Siri, Alexa and other vocal avatars, reaches a more fluid and natural communication with computers, thus converting the dichotomy between man and machine into a harmonious interaction, now heads unequivocally towards a new IT paradigm, where holographic computing will play a key role. The OLOS® platform contributes substantially to this trend in that it infuses computers with human features, by transferring the gestures and expressions of persons of flesh and bones to anthropomorphic holographic interfaces which in turn will use them to interact with real-life humans. In fact, we could say, boldly but with a solid technological background to back the statement, that OLOS® gives reality to an altogether new entity, placed at the exact boundary between nature and technology, namely the holographic human being. Holographic humans qualify as the perfect carriers for the virtual reincarnation of characters handed down from history and tradition. Thus, they provide for an innovative and highly immersive way of experiencing our cultural heritage as something alive and pulsating in the present.

The Flashnews as a Commercial Session of Political Marketing: The Content Analysis of the Embedded Political Narratives in Non-Political Media Products

Political communication in Hungary has undergone a significant change in the 2010s. One element of the transformation is the Flashnews. This media product was launched in March 2015 and since then 40-50 blocks are broadcasted, daily, on 5 channels. Flashnews blocks are condensed news sessions, containing the summary of political narratives. It starts with the introduction of the narrator, then, usually four news topics are presented and, finally, the narrator concludes the block. The block lasts only one minute and, therefore, it provides a blink session into the main narratives of political communication at the time. Beyond its rapid pace, what makes its avoidance difficult is that these blocks are always in the first position in the commercial break of a non-political media product. Although it is only one minute long, its significance is high. The content of the Flashnews reflects the main governmental narratives and, therefore, the Flashnews is part of the agenda-setting capacity of political communication. It reaches media consumers who have limited knowledge and interest in politics, and their use of media products is not politically related. For this audience, the Flashnews pops up in the same way as commercials. Due to its structure and appearance, the impact of Flashnews seems to be similar to commercials, imbedded into the break of media products. It activates existing knowledge constructs, builds up associational links and maintains their presence in a way that the recipient is not aware of the phenomenon. The research aims to examine the extent to which the Flashnews and the main news narratives are identical in their content. This aim is realized with the content analysis of the two news products by examining the Flashnews and the evening news during main sport events from 2016 to 2018. The initial hypothesis of the research is that Flashnews is a contribution to the news management technique for an effective articulation of political narratives in public service media channels.

The Net as a Living Experience of Distance Motherhood within Italian Culture

Motherhood is an existential human relationship that lasts for the whole life and is always interwoven with subjectivity and culture. As a result of the brain drain, the motherhood becomes motherhood at distance. Starting from the hypothesis that re-signification of the mother at distance practices is culturally relevant; the research aims to understand the experience of mother at a distance in order to extrapolate the strategies of management of the empty nest. Specifically, the research aims to evaluate the experience of a brain drain’s mother, who created a blog that intends to take care of other parents at a distance. Actually, the blog is the only artifact symbol of the Italian culture of motherhood at distance. In the research, a Netnographic Analysis of the blog mammedicervelliinfuga.com is offered with the aim of understanding if the online world becomes an opportunity to manage the role of mother at a distance. A narrative interview with the blog creator was conducted and then the texts were analyzed by means of a Diatextual Analysis approach. It emerged that the migration projects of talented children take on different meanings and representations for parents. Thus, it is shown that the blog becomes a new form of understanding and practicing motherhood at a distance.

Robotic Assistance in Nursing Care: Survey on Challenges and Scenarios

Robotic assistance in nursing care is an increasingly important area of research and development. Facing a shortage of labor and an increasing number of people in need of care, the German Nursing Care Innovation Center (Pflegeinnovationszentrum, PIZ) aims to address these challenges from the side of technology. Little is known about nurses experiences with existing robotic assistance systems. Especially nurses perspectives on starting points for the development of robotic solutions, that target recurring burdensome tasks in everyday nursing care, are of interest. This paper presents findings focusing on robotics resulting from an explanatory mixed-methods study on nurses experiences with and their expectations for innovative technologies in nursing care in stationary and ambulant care facilities and hospitals in Germany. Based on the findings, eight scenarios for robotic assistance are identified based on the real needs of practitioners. An initial system addressing a single use-case is described to show perspectives for the use of robots in nursing care.

Effect of Wavy Leading-Edges on Wings in Different Planetary Atmospheres

Today we are unmarking the secrets of the universe by exploring different stars and planets and most of the space exploration is done by unmanned space robots. In addition to our planet Earth, there are pieces of evidence that show other astronomical objects in our solar system such as Venus, Mars, Saturn’s moon Titan and Uranus support the flight of fixed wing air vehicles. In this paper, we take forward the concept of presence of large rounded tubercles along the leading edge of a wing and use it as a passive flow control device that will help in improving its aerodynamic performance and maneuverability. Furthermore, in this research, aerodynamic measurements and performance analysis of wavy leading tubercles on the fixed wings at 5-degree angle of attack are carried out after determination of the flow conditions on the selected planetary bodies. Wavelength and amplitude for the sinusoidal modifications on the leading edge are analyzed and simulations are carried out for three-dimensional NACA 0012 airfoil maintaining unity AR (Aspect Ratio). Tubercles have consistently demonstrated the ability to delay and decrease the severity of stall as per the studies were done in the Earth’s atmosphere. Implementing the same design on the leading edges of Micro-Air Vehicles (MAVs) and UAVs could make these aircrafts more stable over a greater range of angles of attack in different planetary environments of our solar system.

Research Regarding Resistance Characteristics of Biscuits Assortment Using Cone Penetrometer

In the activity of handling and transport of food products, the products may be subjected to mechanical stresses that may lead to their deterioration by deformation, breaking, or crushing. This is the case for biscuits, regardless of their type (gluten-free or sugary), the addition of ingredients or flour from which they are made. However, gluten-free biscuits have a higher mechanical resistance to breakage or crushing compared to easily shattered sugar biscuits (especially those for children). The paper presents the results of the experimental evaluation of the texture for four varieties of commercial biscuits, using the penetrometer equipped with needle cone at five different additional weights on the cone-rod. The assortments of biscuits tested in the laboratory were Petit Beurre, Picnic, and Maia (all three manufactured by RoStar, Romania) and Sultani diet biscuits, manufactured by Eti Burcak Sultani (Turkey, in packs of 138 g). For the four varieties of biscuits and the five additional weights (50, 77, 100, 150 and 177 g), the experimental data obtained were subjected to regression analysis in the MS Office Excel program, using Velon's relationship (h = a∙ln(t) + b). The regression curves were analysed comparatively in order to identify possible differences and to highlight the variation of the penetration depth h, in relation to the time t. Based on the penetration depth between two-time intervals (every 5 seconds), the curves of variation of the penetration speed in relation to time were then drawn. It was found that Velon's law verifies the experimental data for all assortments of biscuits and for all five additional weights. The correlation coefficient R2 had in most of the analysed cases values over 0.850. The values recorded for the penetration depth were framed, in general, within 45-55 p.u. (penetrometric units) at an additional mass of 50 g, respectively between 155-168 p.u., at an additional mass of 177 g, at Petit Beurre biscuits. For Sultani diet biscuits, the values of the penetration depth were within the limits of 32-35 p.u., at an additional weight of 50 g and between 80-114 p.u., at an additional weight of 177g. The data presented in the paper can be used by both operators on the manufacturing technology flow, as well as by the traders of these food products, in order to establish the most efficient parametric of the working regimes (when packaging and handling).

Stochastic Optimization of a Vendor-Managed Inventory Problem in a Two-Echelon Supply Chain

The purpose of this paper is to develop a multi-product economic production quantity model under vendor management inventory policy and restrictions including limited warehouse space, budget, and number of orders, average shortage time and maximum permissible shortage. Since the “costs” cannot be predicted with certainty, it is assumed that data behave under uncertain environment. The problem is first formulated into the framework of a bi-objective of multi-product economic production quantity model. Then, the problem is solved with three multi-objective decision-making (MODM) methods. Then following this, three methods had been compared on information on the optimal value of the two objective functions and the central processing unit (CPU) time with the statistical analysis method and the multi-attribute decision-making (MADM). The results are compared with statistical analysis method and the MADM. The results of the study demonstrate that augmented-constraint in terms of optimal value of the two objective functions and the CPU time perform better than global criteria, and goal programming. Sensitivity analysis is done to illustrate the effect of parameter variations on the optimal solution. The contribution of this research is the use of random costs data in developing a multi-product economic production quantity model under vendor management inventory policy with several constraints.

Validity of Universe Structure Conception as Nested Vortexes

This paper introduces the Nested Vortexes conception of the universe structure and interprets all the physical phenomena according this conception. The paper first reviews recent physics theories, either in microscopic scale or macroscopic scale, to collect evidence that the space is not empty. But, these theories describe the property of the space medium without determining its structure. Determining the structure of space medium is essential to understand the mechanism that leads to its properties. Without determining the space medium structure, many phenomena; such as electric and magnetic fields, gravity, or wave-particle duality remain uninterpreted. Thus, this paper introduces a conception about the structure of the universe. It assumes that the universe is a medium of ultra-tiny homogeneous particles which are still undiscovered. Like any medium with certain movements, possibly because of a great asymmetric explosion, vortexes have occurred. A vortex condenses the ultra-tiny particles in its center forming a bigger particle, the bigger particles, in turn, could be trapped in a bigger vortex and condense in its center forming a much bigger particle and so on. This conception describes galaxies, stars, protons as particles at different levels. Existing of the particle’s vortexes make the consistency of the speed of light postulate is not true. This conception shows that the vortex motion dynamic agrees with the motion of all the universe particles at any level. An experiment has been carried out to detect the orbiting effect of aggregated vortexes of aligned atoms of a permanent magnet. Based on the described particle’s structure, the gravity force of a particle and attraction between particles as well as charge, electric and magnetic fields and quantum mechanics characteristics are interpreted. All augmented physics phenomena are solved.

Rule Insertion Technique for Dynamic Cell Structure Neural Network

This paper discusses the idea of capturing an expert’s knowledge in the form of human understandable rules and then inserting these rules into a dynamic cell structure (DCS) neural network. The DCS is a form of self-organizing map that can be used for many purposes, including classification and prediction. This particular neural network is considered to be a topology preserving network that starts with no pre-structure, but assumes a structure once trained. The DCS has been used in mission and safety-critical applications, including adaptive flight control and health-monitoring in aerial vehicles. The approach is to insert expert knowledge into the DCS before training. Rules are translated into a pre-structure and then training data are presented. This idea has been demonstrated using the well-known Iris data set and it has been shown that inserting the pre-structure results in better accuracy with the same training.

Railway Crane Accident: A Comparative Metallographic Test on Pins Fractured during Operation

Eventually train accidents occur on railways and for some specific cases it is necessary to use a train rescue with a crane positioned under a platform wagon. These tumbled machines are collected and sent to the machine shop or scrap yard. In one of these cranes that were being used to rescue a wagon, occurred a fall of hoist due to fracture of two large pins. The two pins were collected and sent for failure analysis. This work investigates the main cause and the secondary causes for the initiation of the fatigue crack. All standard failure analysis procedures were applied, with careful evaluation of the characteristics of the material, fractured surfaces and, mainly, metallographic tests using an optical microscope to compare the geometry of the peaks and valleys of the thread of the pins and their respective seats. By metallographic analysis, it was concluded that the fatigue cracks were started from a notch (stress concentration) in the valley of the threads of the pin applied to the right side of the crane (pin 1). In this, it was verified that the peaks of the threads of the pin seat did not have proper geometry, with sharp edges being present that caused such notches. The visual analysis showed that fracture of the pin on the left side of the crane (pin 2) was brittle type, being a consequence of the fracture of the first one. Recommendations for this and other railway cranes have been made, such as nondestructive testing, stress calculation, design review, quality control and suitability of the mechanical forming process of the seat threads and pin threads.