nils-herrmann/clean_scirepeval huggingface dataset:
Impact of Social Media on Personality Development
Year: 2014

The aim of the study is to examine the impact of social media on personality development of adolescents and to identify social media factors that influence personality development. A qualitative approach has been adopted in order fully explore the subject matter without any constraints. Data was collected using only peer reviewed Journal Articles and articles from book sections. The grounded theory method was used to reach the conclusion. The findings show that use of social media is extreme in adolescents as they use not only for socializing, but also for communication, entertainment, and all the other activities. The four main social media factors that influence personality development include (i) Culture of Popularity, (ii) Unreal Standards of Appearance, (iii) Approval Seeking Behavior, and (iv) Prevalence of Depression and Anxiety. The research has two main limitations. The first limitation is that the study does not make use of primary data in forms of interviews or observation but it was made sure that only primary sources are used. Secondly, the use of qualitative approach which increases researcher bias. The findings of this study can be used to minimize the negative effects of social media on the personality development of adolescents through educational and intervention plans. The findings show that social media has an adverse effect on the personality development of adolescents. The study specifically identifies the four personality factors that are altered by the excessive use of social media. These findings can be used to develop interventions to minimize this negative impact on adolescents.
Grain structure control during metal 3D printing by high intensity ultrasound
Venue: Nature Communications
Year: 2020

Additive manufacturing (AM) of metals, also known as metal 3D printing, typically leads to the formation of columnar grain structures along the build direction in most as built metals and alloys. These long columnar grains can cause property anisotropy, which is usually detrimental to component qualification or targeted applications. Here, without changing alloy chemistry, we demonstrate an AM solidification control solution to printing metallic alloys with an equiaxed grain structure and improved mechanical properties. Using the titanium alloy Ti 6Al 4V as a model alloy, we employ high intensity ultrasound to achieve full transition from columnar grains to fine ~100 um) equiaxed grains in AM Ti 6Al 4V samples by laser powder deposition. This results in a 12% improvement in both the yield stress and tensile strength compared with the conventional AM columnar Ti 6Al 4V. We further demonstrate the generality of our technique by achieving similar grain structure control results in the nickel based superalloy Inconel 625, and expect that this method may be applicable to other metallic materials that exhibit columnar grain structures during AM.3D printing of metals produces elongated columnar grains which are usually detrimental to component performance. Here, the authors combine ultrasound and 3D printing to promote equiaxed and refined microstructures in a titanium alloy and a nickel based superalloy resulting in improved mechanical properties.
Modeling a Student Classroom Interaction in a Tutorial Like System Using Learning Automata
Venue: IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics)
Year: 2010

Almost all of the learning paradigms used in machine learning, learning automata (LA) and learning theory, in general, use the philosophy of a student (learning mechanism) attempting to learn from a teacher. This paradigm has been generalized in a myriad of ways, including the scenario when there are multiple teachers or a hierarchy of mechanisms that collectively achieve the learning. In this paper, we consider a departure from this paradigm by allowing the student to be a member of a classroom of students, where, for the most part, we permit each member of the classroom not only to learn from the teacher(s) but also to ldquoextractrdquo information from any of his fellow students. This paper deals with issues concerning the modeling, decision making process, and testing of such a scenario within the LA context. The main result that we show is that a weak learner can actually benefit from this capability of utilizing the information that he gets from a superior colleague if this information transfer is done appropriately. As far as we know, the whole concept of Students learning from both a teacher and from a classroom of Students is novel and unreported in the literature. The proposed student classroom interaction has been tested for numerous strategies and for different environments, including the established benchmarks, and the results show that students can improve their learning by interacting with each other. For example, for some interaction strategies, a weak student can improve his learning by up to 73% when interacting with a classroom of students, which includes students of various capabilities. In these interactions, the student does not have a priori knowledge of the identity or characteristics of the students who offer their assistance.
ANALISIS PEMBENTUKAN PORTOFOLIO EFISIEN PADA SEKTOR PERDAGANGAN JASA DAN INVESTASI YANG TERDAFTAR DI BURSA EFEK INDONESIA (BEI) DENGAN MODEL MARKOWITZ
Year: 2014

Analisis portofolio menjelaskan hubungan antara tingkat risiko yang harus ditanggung dengan keuntungan yang diharapkan atas diversifikasi saham. Investor umumnya mengharapkan tingkat pengembalian yang maksimal dengan risiko tertentu. Para calon investor dapat melakukan portofolio (diversifikasi) saham yaitu dengan melakukan investasi lebih dari satu saham dengan tujuan dapat mengurangi risiko kerugian. Tujuan dari penelitian ini adalah untuk mengetahui expected return, tingkat risiko, serta proporsi nilai investasi pada masing masing sub sektor yang menjadi portofolio efisien untuk tipe investor risk seeker dan risk averse dari portofolio yang terbentuk. Jenis data dalam penelitian ini adalah data sekunder yang berupa catatan laporan tertulis yang diterbitkan oleh Bursa Efek Indonesia yang didapat dari media elektronik yaitu internet (www.yahoofinance.com dan www.idx.co.id) Yaitu dengan closing price setiap bulan (48 bulan) periode Juni 2010 Mei 2014. Data yang diperoleh dianalisis dengan model markowitz karena Model Markowitz dapat membantu investor dalam menentukan saham saham yang menjadi portofolio yang efisien. Hasil penelitian menunjukkan bahwa pembentukan portofolio pada Sektor perdagangan jasa dan investasi sektor untuk risk seeker untuk tipe investor risk seeker, Portofolio ke 1 menghasilkan expected return sebesar 4,19% dan risiko sebesar 12,53% Untuk Risk Averse, Portofolio ke 4 dengan proporsi menghasilkan expected return sebesar 3,98% dan risiko sebesar 9,84%
Sleep duration and architecture during ASV for central sleep apnoea in systolic heart failure
Venue: Respiratory Physiology Neurobiology
Year: 2020

Adaptive servoventilation (ASV) effectively treats nocturnal respiratory events in patients with heart failure and reduced ejection fraction (HFrEF) and central sleep apnoea (CSA) but increased mortality has been reported. This study investigated changes in sleep architecture during ASV treatment in HFrEF patients.  A retrospective analysis of polysomnographic datasets for 30 ASV treated patients with stable HFrEF and moderate to severe CSA was performed, including blinded analyses of total sleep time (TST) and percentage of REM and non REM sleep (stages N1 N3) RESULTS Follow up was 109 32 days; mean device usage was 6.0 1.1 h/day. During ASV there was reduction of N1 (34 20%/TST to 13 5%/TST, p 0.001) and N3 sleep (4 6%/TST to 1 4%/TST, p 0.020) and increase of N2 (44 14%/TST to 62 7%/TST, p 0.001) and REM sleep (18 8%/TST to 24 6%/TST, p 0.002) CONCLUSIONS Disturbances of sympatho vagal balance during ASV might help explain increased mortality during ASV. Since sympathetic tone is highest in REM sleep and vagal predominance occurs during N3 sleep, these findings generate new hypotheses for the increased mortality seen in SERVE HF.
Deep Shared Representation Learning for Weather Elements Forecasting
Venue: BNAIC/BENELEARN
Year: 2019

The accuracy and reliability of weather forecasting are of importance for many economic, business and management activities. This paper introduces novel data driven predictive models based on deep convolutional neural networks (CNN) architecture for temperature and wind speed prediction in weather data. In particular, the proposed deep learning framework employs different upgrading versions of the convolutional neural networks i.e. 1d 2d and 3d CNN. The introduced models exploit the spatio temporal multivariate weather data for learning shared representations using historical data and forecasting weather elements for a number of user defined weather stations simultaneously in an end to end fashion. The embedded feature learning component of the models as well as coupling the learned features of different input layers have shown to have a significant impact on the prediction task. The proposed models show promising results compared to the classical neural networks architecture used for modeling nonlinear systems. Two experimental setups have been considered based on a dataset collected from the Weather Underground website at six stations located in Netherlands and Belgium as well as a larger dataset with higher temporal resolution from the National Climatic Data Center (NCDC) at five stations located in Denmark. First, we focus on simultaneously predicting the temperature of two main stations of Amsterdam and Brussels for 1 10 days ahead. The second experiment concerns wind speed prediction at three weather stations located in Denmark for 6 and 12 h ahead. The obtained numerical results show that learning new shared representations of the weather data by means of convolutional operations improves the prediction performance.
The Effect of Empowerment on Nursing Performance, Job Satisfaction, Organizational Commitment, and Turnover Intention in Hospital Nurses
Year: 2011

The purpose of this study was to explore the effect of empowerment on nursing performance, job satisfaction, organizational commitment and turnover intention in hospital nurses.  The subjects were 345 nurses at a general hospital in Dcity. Data were collected by structured questionnaire from January 10 to February 15, 2009. Data were analyzed by using descriptive statistics, ANOVA, Scheffe's test, and Pearson correlation coefficient, multiple regression by SPSS win 17.0 program.  The mean scores were 3.60( .43) of empowerment, 3.80( .38) of nursing performance, 3.49( .55) of job satisfaction, 4.70( .74) of organizational commitment, and 2.34( .84) of turnover intention. Empowerment was correlated with nursing performance, job satisfaction, and organizational commitment positively, but correlated with turnover intention negatively. As a result of multiple regression, empowerment has 34.3% of the explanatory power on nursing performance, 24.0% on job satisfaction, 30.7% on organizational commitment, and 15.6% on turnover intention.  Empowerment was a critical variable affecting nursing job performance, job satisfaction, organizational commitment, and turnover. Also, if various variable active and adequate child care support system, provided conditions continue to study, and adequate and appropriate compensation for nursing performance affecting empowerment are managed, nurses' empowerment level will rise at the same time.
An updated version of "Leader following consensus for linear multi agent systems via asynchronous sampled data control, " IEEE Transactions on Automatic Control, DOI: 10.1109/TAC.2019.2948256
Venue: ArXiv
Year: 2020

In this article, we update the reference  in two aspects. First, we note that in order for the control law (12) in  to be equivalent to the control law (3) in  we need to assume that the samplings for all subsystems must be synchronous, i.e. we need to assume that $T_{i}=T$ for all $i=1,\cdots,N$ Second, we extend our results from periodic sampling to aperiodic sampling.
Fichte's Deduction of the Moral Law
Year: 2019

It is often assumed that Fichte's aim in Part I of the System of Ethics is to provide a deduction of the moral law, the very thing which Kant after years of unsuccessful attempts deemed impossible. On this familiar reading, what Kant eventually viewed as an underivable "fact" (Factum) the authority of the moral law, is what Fichte traces to its highest ground in what he calls the principle of the I as such. However, scholars have largely overlooked a passage in the System of Ethics where Fichte explicitly invokes Kant's doctrine of the fact of reason with approval, claiming that consciousness of the moral law grounds our belief in freedom (GA I/5:65) On the reading I defend in this paper, Fichte's invocation of the Factum is consistent with the structure of Part I when we distinguish (a) the feeling of moral compulsion from (b) the moral law itself.
Toward liveable commercial streets: A case study of Al Karada inner street in Baghdad
Venue: Heliyon
Year: 2019

Nowadays, liveability is a major consideration in upgrading public spaces, especially more sustainable streets. Considerable research has also been conducted to determine the most relevant indicators for more vibrant commercial streets. This paper sheds light on a specific case study in which terrorist attack led to the loss of vitality and ability to attract visitors in one of the most important commercial areas in Baghdad, Al Karada inner street. The paper's aim is to identify indicators for reviving the companionable and sociable life of a street. As a result, it presents many indicators that can be applied to upgrade commercial street vitality by way of a significant, inclusive checklist, which incorporates many aspects. This checklist serves as a comprehensive framework to present needed information, diagnose problems, and identify the strengths and weaknesses of a commercial street's performance to enhance its liveability.
Impact of Managerial Ownership, Financial Leverage, Profitability, Firm Size and Investment Opportunity on Dividend Policy
Year: 2020

The main purpose of this study is to find out the impact of managerial ownership, financial leverage, profitability, firm size and investment opportunity on dividend policy. This study uses the sample of 50 FMCG companies listed in Bombay Stock Exchange during 2013 2018. The results revealed that managerial ownership and Investment opportunity affect the dividend policy in a negative way whereas profitability, leverage and firm size has less or no effect on the dividend policy of the firms.
Learning a Neural network based Representation for Open Set Recognition
Venue: SDM
Year: 2020

Open set recognition problems exist in many domains. For example in security, new malware classes emerge regularly; therefore malware classification systems need to identify instances from unknown classes in addition to discriminating between known classes. In this paper we present a neural network based representation for addressing the open set recognition problem. In this representation instances from the same class are close to each other while instances from different classes are further apart, resulting in statistically significant improvement when compared to other approaches on three datasets from two different domains.
PENGARUH OMNI CHANNEL MARKETING TERHADAP MINAT BELI KONSUMEN (Studi Kasus pada Produk Tabungan Emas PT. Pegadaian Syariah cabang Padayungan)
Year: 2019

Perubahan industri menyebabkan aktifitas organisasi berubah yang dipengaruhi oleh maraknya perkembangan teknologi serta internet tak terkecuali dalam bidang ekonomi dan bisnis. Tingginya tingkat penggunan internet di Indonesia menjadi dasar dari strategi pemasaran perusahaan agar menjangkau lebih luas lagi konsumen potensial di kalangan masyarakat milenial saat ini. Adapun tujuan dari penelitian ini adalah untuk mengetahui dan menganalisis pengaruh Omni Channel Marketing terhadap minat beli konsumen pada Tabungan Emas di PT. Pegadaian Syariah cabang Padayungan. Metode yang digunakan dalam penelitian ini adalah metode survey dengan pendekatan penelitian kuantitatif. Sedangkan untuk menganalisis data yang diperoleh digunakan Analisis Koefisien Korelasi Sederhana= 0,240 Analisis Determinasi= 66,83% Analisis Signifikasi (Uji t) bobot t hitung 2.3096 sedangkan bobot t tabel 1,989 Analisis Signifikasi (Uji F) F hitung 5,6470 lebih besar dari F tabel 5,374 dengan tingkat signifikasi 0,05 Terdapat pengaruh omni channel marketing terhadap minat beli konsumen pada produk tabungan emas di PT. Pegadaian Syariah cabang Padayungan, pengoptimalisasian aplikasi pegadaian digital membuat nasabah semakin terbantu, memberikan pengalaman yang aman dan nyaman membuat mereka bertahan dengan produk dan mampu meningkatkan minat beli konsumen. Penerapan sistem omni channel marketing terhadap minat beli konsumen pada produk tabungan emas di PT. Pegadaian Syariah cabang Padayungan sudah baik. Namun alangkah baiknya pihak perusahaan lebih memperhatikan aspek teknologi dan data yaitu dengan cara memberikan informasi dan pemahaman yang lebih mengenai penggunaan aplikasi digital pegadaian, misalnya seperti membuat video tutorial dan video edukasi agar semua orang dapat dengan mudah mengaksesnya dan secara gratis.
Classifying IoT Devices in Smart Environments Using Network Traffic Characteristics
Venue: IEEE Transactions on Mobile Computing
Year: 2019

The Internet of Things (IoT) is being hailed as the next wave revolutionizing our society, and smart homes, enterprises, and cities are increasingly being equipped with a plethora of IoT devices. Yet, operators of such smart environments may not even be fully aware of their IoT assets, let alone whether each IoT device is functioning properly safe from cyber attacks. In this paper, we address this challenge by developing a robust framework for IoT device classification using traffic characteristics obtained at the network level. Our contributions are fourfold. First, we instrument a smart environment with 28 different IoT devices spanning cameras, lights, plugs, motion sensors, appliances, and health monitors. We collect and synthesize traffic traces from this infrastructure for a period of six months, a subset of which we release as open data for the community to use. Second, we present insights into the underlying network traffic characteristics using statistical attributes such as activity cycles, port numbers, signalling patterns, and cipher suites. Third, we develop a multi stage machine learning based classification algorithm and demonstrate its ability to identify specific IoT devices with over 99 percent accuracy based on their network activity. Finally, we discuss the trade offs between cost, speed, and performance involved in deploying the classification framework in real time. Our study paves the way for operators of smart environments to monitor their IoT assets for presence, functionality, and cyber security without requiring any specialized devices or protocols.
Apical Constriction Reversal upon Mitotic Entry Underlies Different Morphogenetic Outcomes of Cell Division
Venue: Molecular biology of the cell
Year: 2020

During development, coordinated cell shape changes and cell divisions sculpt tissues. While these individual cell behaviors have been extensively studied, how cell shape changes and cell divisions that occur concurrently in epithelia influence tissue shape is less understood. We addressed this question in two contexts of the early Drosophila embryo: premature cell division during mesoderm invagination, and native ectodermal cell divisions with ectopic activation of apical contractility. Using quantitative live cell imaging, we demonstrated that mitotic entry reverses apical contractility by interfering with medioapical RhoA signaling. While premature mitotic entry inhibits mesoderm invagination, which relies on apical constriction, mitotic entry in an artificially contractile ectoderm induced ectopic tissue invaginations. Ectopic invaginations resulted from medioapical myosin loss in neighboring mitotic cells. This myosin loss enabled nonmitotic cells to apically constrict through mitotic cell stretching. Thus, the spatial pattern of mitotic entry can differentially regulate tissue shape through signal interference between apical contractility and mitosis.
Fotovoltaik Panel ile Beslenebilen SynRM Tasarimi ve Kontrolu
Year: 2020

Senkron Reluktans Motor (SynRM) saglam ve basit yapi, dusuk maliyetli uretim, birim hacim basina yuksek moment imkani, kontrol basitligi, alan zayiflatma kabiliyeti ve rotor sargilarinin bulunmamasi nedeniyle azalan kayiplar gibi bircok avantaja sahiptir. Bu yuzden, bu motorlar cok sayida endustriyel ve otomotiv uygulamalar icin ilgi cekici hale gelmeye baslamistir. Dusuk cap ve dusuk gerilime sahip bir motor ile yuksek moment uretilmesi oldukca zordur. Bu makalede; fotovoltaik (PV) panellerin urettigi dusuk gerilim seviyesiyle calisabilen bir SynRM tasarimi amaclanmistir. Bu motor iyi bir dinamige sahip, yuksek kalkis momentli ve yuksek verimli bir motor olarak tasarlanmistir. Motor, akim basina dusen maksimum moment (MTPA) kontrol algoritmasi ile kontrol edilmistir. Ayrica panellerden maksimum guc elde edilebilmesi icin Maksimum Guc Noktasi Izleme (MPPT) algoritmasi kullanilmistir. Bu algoritma motorun hiz referans bilgisini otomatik olarak degistirerek sistemin maksimum verimde calismasini saglamistir. Bu calismada, geleneksek sistemlere gore daha verimli, daha kompakt ve kullanim kolayligi saglayan bir sistem elde edilmistir.
Electronic waste collection systems using Internet of Things (IoT) Household electronic waste management in Malaysia
Year: 2020

Waste electric and electronic equipment or e waste generation has been identified as a key aspect in solid waste management, though e waste disposal in landfills is not suggested due to the toxic chemicals and heavy metals in it. The presence of valuable metals, namely precious and base metals, such as gold and copper, respectively also highlights the importance of effective waste management strategies. Even though some developed countries practice modern household e waste management techniques, including extended producer responsibility (EPR) schemes, household e waste legislative frameworks are not yet fully implemented in Malaysia. In order to support the sustainability of smarter cities concept, household e waste needs to be efficiently managed and this work discusses the application of smart collection systems pertaining to the Malaysian e waste management and recycling sector. A smart household e waste collection box was designed, fitted with e waste level measurement sensors to record the disposal data. A backend server was developed which automatically notifies and schedules e waste collectors to dispatch and collect the e waste when the volume of the collection box reaches a certain threshold (e.g. box is 80% filled) A mobile application was developed in this work and public end users are intended to use it to dispose their household e waste. The smart system was successfully developed as a proof of concept in this work and it could be beneficial to improve the household waste consumer electronics collection in Malaysia.
Estres, respuestas emocionales, factores de riesgo, psicopatologia y manejo del personal de salud durante la pandemia por COVID 19
Year: 2020

El nuevo coronavirus SARS Cov 2, causante de la pandemia por COVID 19, afecta al personal de salud por la repercusion emocional que implica enfrentarse a situaciones complejas y estresantes que retan los mecanismos de regulacion emocional y capacidad de adaptacion a la vida cotidiana para mantener un estado de salud mental optimo.  Describir las reacciones emocionales esperadas ante COVID 19, los factores individuales protectores y de riesgo, la patologia psiquiatrica y las distintas intervenciones que pueden efectuarse en apoyo de las diversas reacciones.  Para los trabajadores de la salud, la pandemia por COVID 19 es un factor de riesgo de problemas de salud mental que requiere evaluacion y atencion oportuna.