The Communication Library DIALOG for iFDAQ of the COMPASS Experiment

Modern experiments in high energy physics impose great demands on the reliability, the efficiency, and the data rate of Data Acquisition Systems (DAQ). This contribution focuses on the development and deployment of the new communication library DIALOG for the intelligent, FPGA-based Data Acquisition System (iFDAQ) of the COMPASS experiment at CERN. The iFDAQ utilizing a hardware event builder is designed to be able to readout data at the maximum rate of the experiment. The DIALOG library is a communication system both for distributed and mixed environments, it provides a network transparent inter-process communication layer. Using the high-performance and modern C++ framework Qt and its Qt Network API, the DIALOG library presents an alternative to the previously used DIM library. The DIALOG library was fully incorporated to all processes in the iFDAQ during the run 2016. From the software point of view, it might be considered as a significant improvement of iFDAQ in comparison with the previous run. To extend the possibilities of debugging, the online monitoring of communication among processes via DIALOG GUI is a desirable feature. In the paper, we present the DIALOG library from several insights and discuss it in a detailed way. Moreover, the efficiency measurement and comparison with the DIM library with respect to the iFDAQ requirements is provided.

Learning to Recommend with Negative Ratings Based on Factorization Machine

Rating prediction is an important problem for recommender systems. The task is to predict the rating for an item that a user would give. Most of the existing algorithms for the task ignore the effect of negative ratings rated by users on items, but the negative ratings have a significant impact on users’ purchasing decisions in practice. In this paper, we present a rating prediction algorithm based on factorization machines that consider the effect of negative ratings inspired by Loss Aversion theory. The aim of this paper is to develop a concave and a convex negative disgust function to evaluate the negative ratings respectively. Experiments are conducted on MovieLens dataset. The experimental results demonstrate the effectiveness of the proposed methods by comparing with other four the state-of-the-art approaches. The negative ratings showed much importance in the accuracy of ratings predictions.

IOT Based Process Model for Heart Monitoring Process

Connecting health services with technology has a huge demand as people health situations are becoming worse day by day. In fact, engaging new technologies such as Internet of Things (IOT) into the medical services can enhance the patient care services. Specifically, patients suffering from chronic diseases such as cardiac patients need a special care and monitoring. In reality, some efforts were previously taken to automate and improve the patient monitoring systems. However, the previous efforts have some limitations and lack the real-time feature needed for chronic kind of diseases. In this paper, an improved process model for patient monitoring system specialized for cardiac patients is presented. A survey was distributed and interviews were conducted to gather the needed requirements to improve the cardiac patient monitoring system. Business Process Model and Notation (BPMN) language was used to model the proposed process. In fact, the proposed system uses the IOT Technology to assist doctors to remotely monitor and follow-up with their heart patients in real-time. In order to validate the effectiveness of the proposed solution, simulation analysis was performed using Bizagi Modeler tool. Analysis results show performance improvements in the heart monitoring process. For the future, authors suggest enhancing the proposed system to cover all the chronic diseases.

Classification Method for Turnover While Sleeping Using Multi-Point Unconstrained Sensing Devices

Elderly population in the world is increasing, and consequently, their nursing burden is also increasing. In such situations, monitoring and evaluating their daily action facilitates efficient nursing care. Especially, we focus on an unconscious activity during sleep, i.e. turnover. Monitoring turnover during sleep is essential to evaluate various conditions related to sleep. Bedsores are considered as one of the monitoring conditions. Changing patient’s posture every two hours is required for caregivers to prevent bedsore. Herein, we attempt to develop an unconstrained nocturnal monitoring system using a sensing device based on piezoelectric ceramics that can detect the vibrations owing to human body movement on the bed. In the proposed method, in order to construct a multi-points sensing, we placed two sensing devices under the right and left legs at the head-side of an ordinary bed. Using this equipment, when a subject lies on the bed, feature is calculated from the output voltages of the sensing devices. In order to evaluate our proposed method, we conducted an experiment with six healthy male subjects. Consequently, the period during which turnover occurs can be correctly classified as the turnover period with 100% accuracy.

Study on Clarification of the Core Technology in a Monozukuri Company

It is important to clarify the company’s core technology in product development process to strengthen their power in providing technology that meets the customer requirement. QFD method is adopted to clarify the core technology through identifying the high element technologies that are related to the voice of customer, and offer the most delightful features for customer. AHP is used to determine the importance of evaluating factors. A case study was conducted by using this approach in Japan’s Monozukuri Company (so called manufacturing company) to clarify their core technology based on customer requirements.

Detecting Rat’s Kidney Inflammation Using Real Time Photoacoustic Tomography

Photoacoustic Tomography (PAT) is a promising medical imaging modality that combines optical imaging contrast with the spatial resolution of ultrasound imaging. It can also distinguish the changes in biological features. But, real-time PAT system should be confirmed due to photoacoustic effect for tissue. Thus, we have developed a real-time PAT system using a custom-developed data acquisition board and ultrasound linear probe. To evaluate performance of our system, phantom test was performed. As a result of those experiments, the system showed satisfactory performance and its usefulness has been confirmed. We monitored the degradation of inflammation which induced on the rat’s kidney using real-time PAT.

Online Prediction of Nonlinear Signal Processing Problems Based Kernel Adaptive Filtering

This paper presents two of the most knowing kernel adaptive filtering (KAF) approaches, the kernel least mean squares and the kernel recursive least squares, in order to predict a new output of nonlinear signal processing. Both of these methods implement a nonlinear transfer function using kernel methods in a particular space named reproducing kernel Hilbert space (RKHS) where the model is a linear combination of kernel functions applied to transform the observed data from the input space to a high dimensional feature space of vectors, this idea known as the kernel trick. Then KAF is the developing filters in RKHS. We use two nonlinear signal processing problems, Mackey Glass chaotic time series prediction and nonlinear channel equalization to figure the performance of the approaches presented and finally to result which of them is the adapted one.

Augmenting Navigational Aids: The Development of an Assistive Maritime Navigation Application

On the bridge of a ship the officers are looking for visual aids to guide navigation in order to reconcile the outside world with the position communicated by the digital navigation system. Aids to navigation include: Lighthouses, lightships, sector lights, beacons, buoys, and others. They are designed to help navigators calculate their position, establish their course or avoid dangers. In poor visibility and dense traffic areas, it can be very difficult to identify these critical aids to guide navigation. The paper presents the usage of Augmented Reality (AR) as a means to present digital information about these aids to support navigation. To date, nautical navigation related mobile AR applications have been limited to the leisure industry. If proved viable, this prototype can facilitate the creation of other similar applications that could help commercial officers with navigation. While adopting a user centered design approach, the team has developed the prototype based on insights from initial research carried on board of several ships. The prototype, built on Nexus 9 tablet and Wikitude, features a head-up display of the navigational aids (lights) in the area, presented in AR and a bird’s eye view mode presented on a simplified map. The application employs the aids to navigation data managed by Hydrographic Offices and the tablet’s sensors: GPS, gyroscope, accelerometer, compass and camera. Sea trials on board of a Navy and a commercial ship revealed the end-users’ interest in using the application and further possibility of other data to be presented in AR. The application calculates the GPS position of the ship, the bearing and distance to the navigational aids; all within a high level of accuracy. However, during testing several issues were highlighted which need to be resolved as the prototype is developed further. The prototype stretched the capabilities of Wikitude, loading over 500 objects during tests in a major port. This overloaded the display and required over 45 seconds to load the data. Therefore, extra filters for the navigational aids are being considered in order to declutter the screen. At night, the camera is not powerful enough to distinguish all the lights in the area. Also, magnetic interference with the bridge of the ship generated a continuous compass error of the AR display that varied between 5 and 12 degrees. The deviation of the compass was consistent over the whole testing durations so the team is now looking at the possibility of allowing users to manually calibrate the compass. It is expected that for the usage of AR in professional maritime contexts, further development of existing AR tools and hardware is needed. Designers will also need to implement a user-centered design approach in order to create better interfaces and display technologies for enhanced solutions to aid navigation.

Supply Chain Resilience Triangle: The Study and Development of a Framework

Supply Chain Resilience has been broadly studied during the last decade, focusing the research on many aspects of Supply Chain performance. Consequently, different definitions of Supply Chain Resilience have been developed by the research community, drawing inspiration also from other fields of study such as ecology, sociology, psychology, economy et al. This way, the definitions so far developed in the extant literature are therefore very heterogeneous, and many authors have pointed out a lack of consensus in this field of analysis. The aim of this research is to find common points between these definitions, through the development of a framework of study: the Resilience Triangle. The Resilience Triangle is a tool developed in the field of civil engineering, with the objective of modeling the loss of resilience of a given structure during and after the occurrence of a disruption such as an earthquake. The Resilience Triangle is a simple yet powerful tool: in our opinion, it can summarize all the features that authors have captured in the Supply Chain Resilience definitions over the years. This research intends to recapitulate within this framework all these heterogeneities in Supply Chain Resilience research. After collecting a various number of Supply Chain Resilience definitions present in the extant literature, the methodology approach provides a taxonomy step with the scope of collecting and analyzing all the data gathered. The next step provides the comparison of the data obtained with the plotting of a disruption profile, in order to contextualize the Resilience Triangle in the Supply Chain context. The tool and the results developed in this research will allow to lay the foundation for future Supply Chain Resilience modeling and measurement work.

“Post-Industrial” Journalism as a Creative Industry

The context of post-industrial journalism is one in which the material circumstances of mechanical publication have been displaced by digital technologies, increasing the distance between the orthodoxy of the newsroom and the culture of journalistic writing. Content is, with growing frequency, created for delivery via the internet, publication on web-based ‘platforms’ and consumption on screen media. In this environment, the question is not ‘who is a journalist?’ but ‘what is journalism?’ today. The changes bring into sharp relief new distinctions between journalistic work and journalistic labor, providing a key insight into the current transition between the industrial journalism of the 20th century, and the post-industrial journalism of the present. In the 20th century, the work of journalists and journalistic labor went hand-in-hand as most journalists were employees of news organizations, whilst in the 21st century evidence of a decoupling of ‘acts of journalism’ (work) and journalistic employment (labor) is beginning to appear. This 'decoupling' of the work and labor that underpins journalism practice is far reaching in its implications, not least for institutional structures. Under these conditions we are witnessing the emergence of expanded ‘entrepreneurial’ journalism, based on smaller, more independent and agile - if less stable - enterprise constructs that are a feature of creative industries. Entrepreneurial journalism is realized in a range of organizational forms from social enterprise, through to profit driven start-ups and hybrids of the two. In all instances, however, the primary motif of the organization is an ideological definition of journalism. An example is the Scoop Foundation for Public Interest Journalism in New Zealand, which owns and operates Scoop Publishing Limited, a not for profit company and social enterprise that publishes an independent news site that claims to have over 500,000 monthly users. Our paper demonstrates that this journalistic work meets the ideological definition of journalism; conducted within the creative industries using an innovative organizational structure that offers a new, viable post-industrial future for journalism.

K-Means Based Matching Algorithm for Multi-Resolution Feature Descriptors

Matching high dimensional features between images is computationally expensive for exhaustive search approaches in computer vision. Although the dimension of the feature can be degraded by simplifying the prior knowledge of homography, matching accuracy may degrade as a tradeoff. In this paper, we present a feature matching method based on k-means algorithm that reduces the matching cost and matches the features between images instead of using a simplified geometric assumption. Experimental results show that the proposed method outperforms the previous linear exhaustive search approaches in terms of the inlier ratio of matched pairs.

Visual and Clinical Outcome in Patients with Corneal Lacerations

In industrialized nations, corneal lacerations are one of the most common reason for hospitalization. This study was designed to study visual and clinical outcome in patients presenting with full thickness corneal lacerations in Indian population and to ascertain the impact of various preoperative and operative factors influencing prognosis after repair of corneal lacerations. Males in third decade with injuries at work with metallic objects were common. Lens damage, hyphema, vitreous hemorrhage, retinal detachment and endophthalmitis were seen. All the patients underwent primary repair within first 24 hours of presentation. At 3 months, 74.3% had a good visual outcome. About 5.7% of patients had no perception of light.In conclusion, various demographic and preoperative factors like age, time of presentation, vision at presentation, length of corneal wound, involvement of visual axis, associated ocular features like hyphaema, lenticular changes, vitreous haemorrhage and retinal detachment are significant prognostic indicators for final visual outcome.

The Sustainable Strategies Research for Renewal of “Villages in City”: A Case Study of Liuzhou in Southwestern China

Transformation under the reconfiguration of urban-rural relation in Liuzhou city has never been as radical and visible as it has been since the tremendous turn of the last century in China. Huanjiang village is located in Linhuashan Scenic Area in the middle east of Liuzhou city, with spectacular landscape and traditional features. Nowadays Huanjiang village has become a so-called "village in city", which is considered full of great potential for development because of the economic value of regional advantages during the urban sprawl. Communities of village found it difficult to acclimatize with the dramatic changes, which later led to numerous problems including ecological damage, unemployment of landless farmers and loss of traditional culture. Government has started up a series of renewal planings to resolve the problems, which are based on advanced technology and conform to sustainable and integrated strategies of city planning considering the original context and historical culture, superseding the traditional arrangements based on the guide of extensive economic growth. This paper aims to elaborate the context of Liuzhou city and Huanjiang village offered to both the traditional and sustainable planning approaches, in order to understand challenges and solutions of the rebuilding process. Through the analysis of the place relevant to architecture, society and culture, it will establish the corresponding systematic strategies. Considering the local features, it concludes with a comprehensive perspective on organic renewal in the case of Huanjiang village.

Sustainability Reporting and Performances of the Companies in the Istanbul Stock Exchange Sustainability Index

In today's business world, in which it is difficult to survive, the economic life of products, services or knowledge is considerably reduced. Competitors produce similar products or extra-featured ones instantly. In this environment, the contribution of companies to the social and economic environment is a preferred criterion by consumers alongside products or services. Therefore, consumers need to obtain more detailed information about companies. Besides, this drastic change in the market encourages companies to become sustainable. Sustainable business means the company puts consumed products back. Corporate sustainability, corresponds to sustainability at the level of the company, and gives equal importance to company growth and profitability together with environmental and social issues. The BIST Sustainability Index started to be calculated by the Istanbul Stock Exchange (BIST) in 2014 to evaluate the sustainability performance of companies in Turkey. The main objective of this study is to present the importance of sustainability reports in Turkey. To this aim, the performances of 15 companies in the BIST Sustainability Index were compared the periods before and after entering the index. On the other hand, sustainability reporting practices should be encouraged to increase studies on this issue. In this context, to remain on the agenda of the issue is a further objective of this study. To achieve these objectives, the financial data of the companies in the period before and after entering to the BIST Sustainability Index were analyzed using t-test in Statistical Package for the Social Sciences (SPSS) package. The results of the study showed that no significant difference between the performances of the companies in terms of the net profit margin, the return on assets and equity capital in these periods could be found. Therefore, it can be said that insufficient importance is given to sustainability issues in Turkey. The reasons for this situation might be considered as a lack of awareness due to the recent introduction and calculation of the index. It is expected that the awareness of firms and investors about sustainability will increase, and that they will demonstrate the necessary importance to this issue over time.

A Case Study of Clinicians’ Perceptions of Enterprise Content Management at Tygerberg Hospital

Healthcare is a human right. The sensitivity of health issues has necessitated the introduction of Enterprise Content Management (ECM) at district hospitals in the Western Cape Province of South Africa. The objective is understanding clinicians’ perception of ECM at their workplace. It is a descriptive case study design of constructivist paradigm. It employed a phenomenological data analysis method using a pattern matching deductive based analytical procedure. Purposive and s4nowball sampling techniques were applied in selecting participants. Clinicians expressed concerns and frustrations using ECM such as, non-integration with other hospital systems. Inadequate access points to ECM. Incorrect labelling of notes and bar-coding causes more time wasted in finding information. System features and/or functions (such as search and edit) are not possible. Hospital management and clinicians are not constantly interacting and discussing. Information turnaround time is unacceptably lengthy. Resolving these problems would involve a positive working relationship between hospital management and clinicians. In addition, prioritising the problems faced by clinicians in relation to relevance can ensure problem-solving in order to meet clinicians’ expectations and hospitals’ objective. Clinicians’ perception should invoke attention from hospital management with regards technology use. The study’s results can be generalised across clinician groupings exposed to ECM at various district hospitals because of professional and hospital homogeneity.

Achievements of Healthcare Services Vis-À-Vis the Millennium Development Goals Targets: Evidence from Pakistan

This study investigates the impact of public healthcare facilities and socio-economic circumstances on the status of child health in Pakistan. The complete analysis is carried out in correspondence with fourth and sixth millennium development goals. Further, the health variables chosen are also inherited from targeted indicators of the mentioned goals (MDGs). Trends in the Human Opportunity Index (HOI) for both health inequalities and coverage are analyzed using the Pakistan Social and Living Standards Measurement (PLSM) data set for 2001-02 to 2012-13 at the national and provincial level. To reveal the relative importance of each circumstance in achieving the targeted values for child health, Shorrocks decomposition is applied on HOI. The annual point average growth rate of HOI is used to simulate the time period for the achievement of target set by MDGs and universal access also. The results indicate an improvement in HOI for a reduction in child mortality rates from 52.1% in 2001-02 to 67.3% in 2012-13, which confirms the availability of healthcare opportunities to a larger segment of society. Similarly, immunization against measles and other diseases such as Diphtheria, Polio, Bacillus Calmette-Guerin (BCG), and Hepatitis has also registered an improvement from 51.6% to 69.9% during the period of study at the national level. On a positive note, no gender disparity has been found for child health indicators and that health outcome is mostly affected by the parental and geographical features and availability of health infrastructure. However, the study finds that this achievement has been uneven across provinces. Pakistan is not only lagging behind in achieving its health goals, disappointingly with the current rate of health care provision, but it will take many additional years to achieve its targets.

Developing Creative and Critically Reflective Digital Learning Communities

This paper is a qualitative case study analysis of the development of a fully online learning community of graduate students through arts-based community building activities. With increasing numbers and types of online learning spaces, it is incumbent upon educators to continue to push the edge of what best practices look like in digital learning environments. In digital learning spaces, instructors can no longer be seen as purveyors of content knowledge to be examined at the end of a set course by a final test or exam. The rapid and fluid dissemination of information via Web 3.0 demands that we reshape our approach to teaching and learning, from one that is content-focused to one that is process-driven. Rather than having instructors as formal leaders, today’s digital learning environments require us to share expertise, as it is the collective experiences and knowledge of all students together with the instructors that help to create a very different kind of learning community. This paper focuses on innovations pursued in a 36 hour 12 week graduate course in higher education entitled “Critical and Reflective Practice”. The authors chronicle their journey to developing a fully online learning community (FOLC) by emphasizing the elements of social, cognitive, emotional and digital spaces that form a moving interplay through the community. In this way, students embrace anywhere anytime learning and often take the learning, as well as the relationships they build and skills they acquire, beyond the digital class into real world situations. We argue that in order to increase student online engagement, pedagogical approaches need to stem from two primary elements, both creativity and critical reflection, that are essential pillars upon which instructors can co-design learning environments with students. The theoretical framework for the paper is based on the interaction and interdependence of Creativity, Intuition, Critical Reflection, Social Constructivism and FOLCs. By leveraging students’ embedded familiarity with a wide variety of technologies, this case study of a graduate level course on critical reflection in education, examines how relationships, quality of work produced, and student engagement can improve by using creative and imaginative pedagogical strategies. The authors examine their professional pedagogical strategies through the lens that the teacher acts as facilitator, guide and co-designer. In a world where students can easily search for and organize information as self-directed processes, creativity and connection can at times be lost in the digitized course environment. The paper concludes by posing further questions as to how institutions of higher education may be challenged to restructure their credit granting courses into more flexible modules, and how students need to be considered an important part of assessment and evaluation strategies. By introducing creativity and critical reflection as central features of the digital learning spaces, notions of best practices in digital teaching and learning emerge.

Structure-Activity Relationship of Gold Catalysts on Alumina Supported Cu-Ce Oxides for CO and Volatile Organic Compound Oxidation

The catalytic oxidation of CO and volatile organic compounds (VOCs) is considered as one of the most efficient ways to reduce harmful emissions from various chemical industries. The effectiveness of gold-based catalysts for many reactions of environmental significance was proven during the past three decades. The aim of this work was to combine the favorable features of Au and Cu-Ce mixed oxides in the design of new catalytic materials of improved efficiency and economic viability for removal of air pollutants in waste gases from formaldehyde production. Supported oxides of copper and cerium with Cu: Ce molar ratio 2:1 and 1:5 were prepared by wet impregnation of g-alumina. Gold (2 wt.%) catalysts were synthesized by a deposition-precipitation method. Catalysts characterization was carried out by texture measurements, powder X-ray diffraction, temperature programmed reduction and electron paramagnetic resonance spectroscopy. The catalytic activity in the oxidation of CO, CH3OH and (CH3)2O was measured using continuous flow equipment with fixed bed reactor. Both Cu-Ce/alumina samples demonstrated similar catalytic behavior. The addition of gold caused significant enhancement of CO and methanol oxidation activity (100 % degree of CO and CH3OH conversion at about 60 and 140 oC, respectively). The composition of Cu-Ce mixed oxides affected the performance of gold-based samples considerably. Gold catalyst on Cu-Ce/γ-Al2O3 1:5 exhibited higher activity for CO and CH3OH oxidation in comparison with Au on Cu-Ce/γ-Al2O3 2:1. The better performance of Au/Cu-Ce 1:5 was related to the availability of highly dispersed gold particles and copper oxide clusters in close contact with ceria.

Load Forecasting in Microgrid Systems with R and Cortana Intelligence Suite

Energy production optimization has been traditionally very important for utilities in order to improve resource consumption. However, load forecasting is a challenging task, as there are a large number of relevant variables that must be considered, and several strategies have been used to deal with this complex problem. This is especially true also in microgrids where many elements have to adjust their performance depending on the future generation and consumption conditions. The goal of this paper is to present a solution for short-term load forecasting in microgrids, based on three machine learning experiments developed in R and web services built and deployed with different components of Cortana Intelligence Suite: Azure Machine Learning, a fully managed cloud service that enables to easily build, deploy, and share predictive analytics solutions; SQL database, a Microsoft database service for app developers; and PowerBI, a suite of business analytics tools to analyze data and share insights. Our results show that Boosted Decision Tree and Fast Forest Quantile regression methods can be very useful to predict hourly short-term consumption in microgrids; moreover, we found that for these types of forecasting models, weather data (temperature, wind, humidity and dew point) can play a crucial role in improving the accuracy of the forecasting solution. Data cleaning and feature engineering methods performed in R and different types of machine learning algorithms (Boosted Decision Tree, Fast Forest Quantile and ARIMA) will be presented, and results and performance metrics discussed.

Gated Communities and Sense of Community: A Review on the Social Features of Gated Communities

Since the mid-1970s, gated communities distributed in Latin America. They are a kind of residential development where there are privatized public spaces, and access to the area is restricted. They have specific impacts on the neighborhoods that located outside their walls such as threatening security, limiting access, and spreading social inequality. This research mainly focused on social features of gated community as; segregation, fragmentation, exclusion, specifically on sense of community and typology of gated communities. The conclusion will clarify the pros and cons of gated communities and how it could be successful or not.