Miracle-dz/UniFAR-FTUs huggingface dataset:
The Impact of Shared and Personal Devices on Collaborative Process and Performance

On a daily basis humans interact with an increasing variety of personal electronic devices, ranging from laptops, tablets, smartphones, and e-readers to shared devices such as projected displays and interactive, digital tabletops. An emerging area of study focuses on understanding how these devices can be used together to support collaborative work. Where prior research has shown benefits of devices used individually, there is currently a lack of understanding of how devices should be used in conjunction to optimize a group’s performance. In particular, the research presented in this dissertation combines qualitative and quantitative analyses of group work in three empirical studies to link the use of shared and personal devices to changes in group performance and process. In the first study, participants performed an optimization task with either a single, shared projected display or with the shared, projected display and personal laptops. Analyses of study data indicated that when personal displays were present, group performance was improved for the optimization task (p = 0.025). However, personal devices also reduced a group’s ability to coordinate (p = 0.016). Additionally, when personal devices were present, individuals primarily used those devices instead of dividing time between their laptops and the shared display. To further investigate the support that shared displays provide groups, and in particular, how shared displays might support group work in multi-display settings, a follow-up study was conducted. The second study investigated how two di↵erent types of shared displays supported group work. In particular, shared workspaces, which allowed multiple users to simultaneously interact with shared content, and status displays, which provided awareness of the overall problem state to groups, were investigated. While no significant impact on group performance was observed between the two shared display types, qualitative analysis of groups working in these conditions provided insight into how the displays supported collaborative activities. Shared workspace displays provided a visual reference that aided individuals in grounding communication with their collaborators. On the other hand, status displays enabled the monitoring of a group’s overall task progress. Regardless of which display was present, an individual’s gaze and body position relative to the shared display supported the synchronization of group activities. Finally, where the previous two studies identified collaborative activities that were supported by the use of shared and personal displays, the experimental task performed by participants did not explore the transfer of task materials between shared and personal devices or alternative personal and shared devices. The third study addressed these limitations through the adoption of a new experimental task that enabled the exploration of how the manipulation of task artefacts supported
Hair Cortisol and Health-Related Quality of Life in Children with Mental Disorder

Introduction Children living with mental disorder are at risk for lower health-related quality of life (HRQoL) compared to their peers. While evidence suggests that cortisol dysregulation is implicated in the onset of mental disorder, the extent to which cortisol is associated with HRQoL is largely unknown. Further, it remains unknown how comorbid physical illness may alter this relationship. This study examined whether the presence of a comorbid physical illness moderated the association between hair cortisol concentration (HCC) and HRQoL among children with mental disorder. Methods One-hundred children (4-17 years) receiving care from a pediatric hospital were recruited. The Mini International Neuropsychiatric Interview was used to measure mental disorder and the KIDSCREEN-27 to assess HRQoL. Cortisol extracted from children's hair was assayed using high-sensitivity ELISA. Multiple regression analyses tested the association between HCC and HRQoL. Results Presence of a physical illness was found to moderate the relationship between HCC and HRQoL in the domain of peers and social support [comorbidity: β = −0.57 (−0.97, −0.17); no comorbidity: β = 0.22 (−0.11, 0.55)]. Conclusion The association between HCC and HRQoL in children with mental disorder is moderated by the presence of a physical illness, such that in children with comorbid physical and mental disorder, elevated HCC is associated with lower HRQoL. Approaches that reduce stress in these children may help promote optimal well-being. More research investigating physiological stress and psychosocial outcomes in children with mental disorder, particularly those with comorbid physical illness, is needed.
DESAIN SISTEM INVERTER-PV MENGGUNAKAN ARTIFICIAL NEURAL NETWORKS UNTUK INJEKSI DAYA AKTIF DAN REAKTIF

Pendekatan umum pada pembangkitan tenaga listrik adalah dengan menempatkan suatu plant sentral yang mendistribusikan listrik pada jaringan transmisi dan distribusi. Penelitian ini dilakukan untuk mendesain dan mensimulasikan modul photovoltaic ( PV ) yang dicoupling dengan modul mppt berupa boost converter dan modul injeksi daya aktif dan reaktif berupa voltage source inverter yang pada akhirnya terhubung pada grid utility yaitu jaring distribusi PLN. Modul Photovoltaic umumnya digunakan untuk memenuhi keperluan daya aktif baik itu pada jaringan ataupun pada modul beban elektrik yang terhubung pada grid utility. Desain Inverter dan Konverter Boost pada penelitian ini digunakan untuk dapat mengatur daya aktif dan daya reaktif yang masuk menuju grid. Kontrol MPPT dari Konverter Boost akan dikendalikan menggunakan Artificial Neural Network (ANN) dan injeksi daya aktif dan reaktif pada grid akan diregulasi melalui inverter sumber tegangan dikendalikan mengunakan ANN dengan referensi daya dari Photovoltaic. Hasil simulasi menunjukkan Modul Photovoltaic mencapai daya optimal pada irradiasi 1000 W/m2 dan suhu 35 oC PV sebesar 1.24 kW dengan efisiensi sistem PV-Inverter memiliki akurasi output daya yang tinggi mencapai 99,97 % untuk output daya 1168,192 Watt dengan akurasi daya reaktif mencapai 99 %. Performansi respon perubahan daya terhadap Irradiance juga relatif cepat dengan rentan waktu 0,023 detik terhadap perubahan daya Inverter baik itu aktif (P) ataupun reaktif (Q). Sistem juga mampu mempertahankan kondisi faktor daya pada grid mendekati 0,9 dengan perubahan irradiance dari 1000 W/m2 – 500 W/m2 lalu menuju 900 W/m2 dengan waktu steady rata – rata antar tenggang waktu perubahan kurang dari 0,14 detik.
In ovo feeding technology: Embryonic development, Hatchability and Hatching quality of broiler chicks

: This paper reviewed the effects of in ovo feeding application on incubation performance and chick quality in broilers. Effectiveness of incubation and chick quality in commercial chicken broiler production have a decisive role in production cost as well as efficiency and are a prerequisite for sustainable production. To date, several studies have been done to improve incubation performance and chick quality, and significant gains have been achieved in this area in the last fifty years. The average hatchability and survivability in the sector have reached 85%–90% and 90%–95% respectively, and with new research, theoretical limits have been closely approached. In ovo feeding, one of the newest and technical applications in the incubation sector which successfully implements different methods and technologies in the area of performance and quality improvement has not yet been commercialized. Although in ovo feeding effects on chick weight and hatch properties have been evaluated and scientifically positive in some researches, sufficient progress for the spread of the application in the field has not been registered. Therefore, it is useful to continue studies on this subject, testing two or three interactions together with other supportive applications, and to investigate possible synergistic effects.
Social learning spaces in the Li Ka Shing Library

This paper describes the efforts made by the Li Ka Shing Library, Singapore Management University, in the design, creation and continual improvements of its spaces to meet the needs of its community. The Collaborative Study Area was presented as an example of introducing social learning spaces into the Library. We conducted a survey to measure the satisfaction with our spaces and the activities carried out in the Library. In striving to become a research, social and event space for its community, the Library is also used as an event and training space. This article was presented as a paper at the LAS Conference in May 2008.
Scenario Prediction of Japanese Software Industry Through Hybrid Method

This paper aims at considering the possibility of the future scenario predictions of Japanese software industry through hybrid method. Thus, we try to preliminarily develop a new research framework by connecting the data obtained by large-scale fact-finding investigations, the statistical analyses results using the dynamic modeling, and the future scenarios of Japanese software industry through the simulation. First, we designed a large-scale social survey of the enterprise software industry in Japan, administered it, and developed a measurement tool of the software engineering capabilities with Ministry of Economy, Trade and Industry (METI). Second, we empirically verified that the human resource development of the IT firms improves the operational software engineering capabilities, and that the enhancement of the software engineering capabilities tends to improve the business performance of the IT firms in long term using the dynamic modeling. Third, we are trying to visualize the future scenario of Japanese software industry through the agent-based simulation. This research includes the following original characteristics of academic research and expected results. First, the research suggests the guideline of the global technological strategy for Japan’s software industry to ensure sustainable competitive advantage through the connection among large-scale social surveys, statistical analyses, and future prospects. Second, the research is a challenge for evidence-based visualization of industrial growth scenario by integrating society’s intellectual caliber, which has evolved individually, such as fact-finding investigation conducted with METI, management theory, statistical analyses, and social simulation models. Third, the research has a possibility of evolving of the methods of designing for management of technology as a national strategy, from the viewpoint of management of technology, such as scale of players, technology paradigm shifts, global competitions and collaborations. Fourth, the methods through the connection among large-scale social surveys, statistical analyses, and future prospects, developed in the software industry in Japan can be expanded to any other sectors in any countries.
On Track with the Japanese: A Case-By-Case Approach to Building Successful Relationships

In On Track with the Japanese, Patricia Gercik, Managing Director of the M.I. T. Japan Program, offers us twenty-three portraits of men and women who have succeeded - or failed - in forging personal business ties with the Japanese. With skillfully written anecdotes Gercik teaches Westerners how to avoid cross-cultural pitfalls, overcome communication barriers, and build networks on a foundation of trust. According to Gercik, the insider/outsider nature of Japanese society requires a graduated approach to relationships, which she has divided into four stages: "Know Me, " "Trust Me, " "Believe Me, " and "Marry Me. " By emphasizing consistent patterns of Japanese business etiquette in a wide variety of settings, Gercik provides a hands-on, interactive approach to the inner workings of a complex and often frustrating society.
A Hybrid Technique using CNN+LSTM for Speech Emotion Recognition

Automatic speech emotion recognition is a very necessary activity for effective human-computer interaction. This paper is motivated by using spectrograms as inputs to the hybrid deep convolutional LSTM for speech emotion recognition. In this study, we trained our proposed model using four convolutional layers for high-level feature extraction from input spectrograms, LSTM layer for accumulating long-term dependencies and finally two dense layers. Experimental results on the SAVEE database shows promising performance. Our proposed model is highly capable as it obtained an accuracy of 94.26%.
Recent abnormal hydrologic behavior of Tibetan lakes inferred from multi-mission altimetry and its driving force analyses

The inland lakes in the Tibetan Plateau (TP), with closed catchments and minimal human disturbance, are important indicators to climate change. However, examination of the spatiotemporal patterns of the Tibetan lake changes, especially for water level variation, was usually limited by inadequate measurement accessibility. This obstacle has been remedied by the developing satellite altimetry observations. The more recent studies revealed the growth tendency of lakes in the central TP had been decelerated or reversed during the period 2010-2016. It has not been systematically investigated whether the deceleration or hiatus would last in the following years thus far. This study aims to combine the traditional and recently-advanced altimetry observations to update our understanding of Tibetan lake changes in recent years. The results reveal that water level changes of the 22 examined lakes showed abrupt rises during the period 2016-2018, but the onsets and magnitudes of the rises varied among the lakes. During the study period, the water level of the nine lakes in the northern TP displayed a drastic rising trend with an average rate of 0.82 m/a. In the central TP, the lake level changes were generally divided into two categories. The water levels for the lakes in the western CTP rose rapidly, while in the eastern CTP, the lake water levels rose slowly with an average rising rate less than 0.40 m/a. The water levels for lakes in the northeastern TP and northwestern TP kept a stably rising tendency. According to the results of climate analysis, the spatial diﬀerences of the lake level rise rates were primarily caused by the spatial and temporal changes of precipitation over the TP, which may be related to the large-scale atmospheric circulation aﬀected by the El Ni˜no and La Ni˜na events. Abstract: The inland lakes in the Tibetan Plateau (TP), with closed catchments and minimal human disturbance, are important indicators to climate change. However, examination of the spatiotemporal patterns of the Tibetan lake changes, especially for water level variation, was usually limited by inadequate measurement accessibility. This obstacle has been remedied by the developing satellite altimetry observations. The more recent studies revealed the growth tendency of lakes in the central TP had been decelerated or reversed during the period 2010-2016. It has not been systematically investigated whether the deceleration or hiatus would last in the following years thus far. This study aims to combine the traditional and recently-advanced altimetry observations to update our understanding of Tibetan lake changes in recent years. The results reveal that water level changes of the 22 examined lakes showed abrupt rises during the period 2016-2018, but the onsets and magnitudes of the rises varied among the lakes. During the study period, the water level of the nine lakes in the northern TP displayed a drastic rising trend with an average rate of 0.82 m/a. In
Resource allocation in energy sustainable wireless mesh networks

Wireless LAN (WLAN) mesh networks are now being used to deploy Wi-Fi coverage in a wide variety of outdoor applications. In these types of networks, conventional WLAN mesh nodes must be operated using continuous electrical power connections. This requirement may often be very expensive, especially when the network includes expansive outdoor wireless coverage areas. An alternative is to operate some of the WLAN mesh nodes using an energy sustainable source such as solar or wind power. This eliminates the need for a fixed power connection, making the node truly tether-less and allowing for more flexibility in node positioning. The cost of the battery and the solar panel or wind turbine can be a significant fraction of the total node cost, therefore the resource allocation must be performed optimally. In this thesis we investigate this problem. First, we present geographic provisioning results for solar and wind powered WLAN mesh nodes. The results suggest that in certain geographic locations a hybrid wind/solar powered WLAN mesh node is the optimum minimum cost configuration. The results also provide strong motivation for introducing power saving to the IEEE 802.11 standard. We then consider the problem of cost-optimal node placement in a hybrid network containing traditional and energy sustainable nodes. Our results show that there is a significant improvement in cost that can be obtained using the proposed methodology. Finally, we consider the problem of energy management in these networks. A control algorithm is proposed that uses access to publicly available meteorological databases. We show that the proposed algorithm minimizes node outage and performs favorably compared to the analytic performance bounds. Overall, the work in this thesis develops analytical and simulation models which investigate the key aspects pertaining to resource allocation in energy sustainable WLAN mesh networks.
The effect of conglomeration on integrated media communication firms

RESEARCH PAPER: The Effect of Conglomeration on Integrated Media Communication Firms STUDENT: Tyler Bohlman DEGREE: Master of Arts COLLEGE: College of Communication and Information and Media DATE: December, 2013 PAGES: 71 This study has presented a thorough investigation of two Indianapolis-based Integrated Media Communications (IMC) firms and how their internal operations are influenced by the act of conglomeration. Conglomeration is a growing trend in IMC firms and this study provides more information on how the act of conglomeration affects how a business is run. This study used the case study method to focus on two companies, one conglomerated and one independent. By focusing on each company's client relations, internal communications, and infrastructure, this study was able to determine that the act of conglomeration has a strongly possible, but not definitive, effect on business. Given the case study method the results are not overtly generalizable to a larger sample; however the results given show that conglomeration does have an effect on IMC firms and provides a starting point for future research.
ASE Guide to Primary Science Education

Wynne Harlen (Ed) Association of Science Education ISBN: 086357405X £20.00 219pp Reviewed by Simon Horbury Ann Oliver David Fulton Publishers ISBN: 1843122596 £17.00 213pp Reviewed by Brian J Ford Joseph S. Elias Greenwood Publishing Group ISBN: 9780313338960 £28.99 218pp Reviewed by Simon Horbury Alan Gunn John Wiley & Sons Ltd ISBN: 0470012773 (paperback) £24.95 304pp Reviewed by Gill Hickman Kirstin Dow and Thomas E Downing Earthscan ISBN: 1844073769 (paperback) £12.00 112pp Reviewed by Simon Napper Dr Tony Smith (Ed) Dorling Kindersley ISBN: 9781405314664 £25.00 240pp Reviewed by Chris Gray
Time domain electromagnetics

Introduction. Wire Structure: TDIE Solution. Infinite Conducting Cylinders: TDIE Solution. Finite Conducting Bodies:TDIE Solution. Dielectric Bodies: TDIE Solution. Finite Difference Time Domain Method. Transmission Line Modeling Method. Finite-Element Time Domain Method. Finite-Volume Time Domain Method. Index.
A fast object detector based on high-order gradients and Gaussian process regression for UAV images

Unmanned aerial vehicles (UAVs) acquire images characterized by an exceptional level of detail, which calls for processing and analysis methods capable of efficiently exploiting their rich information content. In particular, the detection of specific classes of objects (e.g. cars, roofs) represents an important but challenging task for these images. Most of the related literature has aimed at proposing methods capable of providing satisfactory detection accuracies. However, they typically refer to a specific class of objects and give little attention to the processing time. In this work, we present a novel and fast methodological alternative. In addition to being particularly fast, the proposed method is a general detection approach that can be customized to any class of objects after an opportune training phase. It consists of the design of a non-linear filter that combines image gradient features at different orders and Gaussian process (GP) modelling. High-order image gradients permit one to capture detailed information regarding the structure of the investigated class of objects. The GP model fed with high-order gradients yields an estimate of the presence of the object of interest for a given position of the sliding window within the image. Two separate sets of experiments were conducted, each aiming at assessing the proposed method to detect a given class of objects common in urban scenarios, namely vehicles and solar panels, respectively. Results on real UAV georeferenced images characterized by 2 cm resolution and by three channels (red, green, and blue (RGB)) are provided and discussed, showing particularly interesting properties of the detector.
Predicting Healthcare-Associated Infections at Admission: Implications for Nursing Care.

BACKGROUND Accurate, real-time models to predict hospital adverse events could facilitate timely and targeted interventions to improve patient outcomes. Advances in computing enable the use of supervised machine learning (SML) techniques to predict hospital-onset infections. OBJECTIVES The purpose of this study was to trial SML methods to predict urinary tract infections (UTI) during inpatient hospitalization at the time of admission. METHOD In a large cohort of adult hospitalizations in three New York City acute care facilities (N = 897,344), we used two SML methods-neural networks and decision trees-to predict having a hospital-onset UTI using data available and accessible on the first day of admission at healthcare facilities in the United States. RESULTS Performance for both neural network and decision tree models were superior compared to logistic regression methods. The decision tree model had a higher sensitivity compared to neural network but a lower specificity. DISCUSSION SML methods show potential for automated accurate UTI risk stratification using electronic data routinely available at admission; this could relieve nurses from the burden of having to complete and document additional risk assessment forms in the electronic medical record. Future studies should pilot and test interventions linked to the risk stratification results, such as short nursing educational modules or alerts triggered for high-risk patients.
Noise reduction in video images using coring on QMF pyramids

This thesis investigates a technique known as “coring” which can be used to reduce noise in two-dimensional video images. Coring passes the high spatial frequency components of a noisy image through a non-linear “coring function. ” This function operates on each pixel and is a function of pixel intensity. This thesis provides a theoretical justification for the success of coring in noise reduction. Coring functions are generated using the theoretical results and then tested on a set of images. Finally, this thesis develops an algorithm for noise reduction given a statistical characterization of the noise. Thesis Supervisor: Edward H. Adelson Title: Associate Professor