Miracle-dz/UniFAR-FTUs huggingface dataset:
AN IMAGE RETRIEVAL FRAMEWORK: A REVIEW

Content-Based Image Retrieval is a process to retrieve the similar images from the huge set of image database corresponding the query image. In CBIR Visual features of the input image are extracted and on the basis of similarity matching algorithm, the required precise image are extracted. To understand the evaluation and evolution of CBIR system various research were studied and various research is going on this way also. In this paper, we have discussed some of the popular pixel level feature extraction techniques for Content-Based Image Retrieval and we also present here about the performance of each technique.
IMPORTANCE OF HUMAN CAPITAL DEVELOPMENT AND COMPETITIVENESS IN ENHANCING COMPETENCY LEVEL AMONG MALAYSIA UNIVERSITY GRADUATES: LITERATURE REVIEW

The investments in higher education and human capital development in enhancing the competency level among university graduates is one of the main issues in Malaysia. Through this human capital development, the country can generate more competitive graduates with the aims to meet current challenges in a competitive job market. However, based on a secondary review, this research found that the level of competency among graduates assessed through their knowledge, skills and attitudes to manage their field of work not only requires the aspects of human capital such as technical skills, interpersonal skills and conceptual skills, but also the development of competitive attitudes among graduates also need to be emphasized. Therefore, this article review outlines the dimension of emerging human capital and competitiveness aspects with the purpose to improve the competency level among university graduates. In addition, this research proposes a conceptual framework to increase the level of competency among university graduates. Finally, the researchers also give some suggestions to reduce unemployment rates among current university graduates.
Ship target recognition based on multi-spectral infrared images

When facing sea-sky background, island-shore background and other complex conditions, recognition rate and false alarm rate of the existing ship target recognition system based on a single wide-wave infrared image will be affected. For solving the above problems, this paper has studied the method of ship target recognition based on multi-spectral infrared images. The image data set of 5 medium-wave infrared images was collected and the samples data set was constructed by annotating the multi-spectral images manually. Firstly, Dense SIFT feature of each infrared image was extracted. Secondly, PCA was applied to each SIFT feature, reducing its dimensionality form 128 to 64. Then the spatial and spectral position information of each SIFT feature was integrated into the feature vector. Based on the Gaussian mixture model, the feature vectors of the multi-spectral images were encoded to obtain the Fisher vector representing the target. Finally, the linear SVM classifier was used to identify Fisher vector and further to recognize the target. Experimental results show that compared with single spectral infrared image, the recognition rate based on multi-spectral infrared images is higher. The recognition rate of the proposed algorithm reaches 0.97. Research indicates this paper provides a new method for ship target recognition based on multi-spectral infrared images.
Exploring TPACK domains of Malaysian non-option ESL teachers in an online flipped learning course through Blendspace

The purpose of this paper is to explore teachers� Technological Pedagogical and Content Knowledge (TPACK) domains in planning digital tools-based activities. It discusses a small part of a major study that investigated Malaysian non-option ESL teacher�s flipped ESL instructional design of teaching and learning in their own classroom context. �Participants were involved in this case study. The miniscule analysis was done for a digital tool called Blendspace (a learning management system � LMS) in order to investigate teacher�s classroom activity plans. The digital tools introduced to the participants were meant to support their ESL flipped learning instructional design. Findings show that new input ameliorated the existing TK domain and made it developmental. This has resulted an improvised TPACK which I coined a term �Augmented TPACK� � an inclusive TPACK domains that consists of developmental TK and non-developmental PK and CK. Participants used Augmented TPACK to plan digital tools-based activity.
Are two heads better than one? Systems factorial technology provides new insights on the group decision-making process

Introduction Are two heads better than one? Aggregating group-level decisions are considered to be superior to individual decisions when response accuracy is considered. This is so-called the wisdom of crowds’ effect. Researchers have investigated the factors that may influence the decision performance when two observers (Bahrami et al., 2010) work together on perceptual decision-making. For example, Bahrami et al., (2010) found that two heads were definitely better than one if two observers had nearly equal visual sensitivity and communicated freely. Once if one observer had much higher sensitivity than the other, group decisions would be worse than individual decisions. However, previous studies made inferences primarily based on the accuracy-based measures. It is still unclear whether group decisions are more efficient than individual decisions. An efficiency assessment requires both response time and accuracy measures to be jointly considered. Therefore, we applied a novel and diagnostic reaction-time tool, systems factorial technology (SFT, Townsend & Nozawa, 1995) to study the efficiency of group decision-making by assessing the measure of processing capacity. The group-level capacity is defined as the ratio of the observed group processing efficiency to the baseline performance predicted from the unlimited-capacity independent parallel model assuming that individuals work independently. Presumably, groups with high efficiency would exhibit large processing capacity, i.e., supercapacity. Two experiments were conducted. An oddball detection task as used in Bahrami et al. (2010) and a Gabor patch detection task as used in Barr and Gold (2014) were tested in separate experiments, respectively. If there is a group advantage in decision-making, we would expect to observe capacity value to be larger than 1, suggesting supercapacity processing. In addition, we would expect a positive correlation between the accuracy-based measure and workload capacity.
Does Industrial Policy Play an Important Role in Enterprise Innovation?

ABSTRACT Using a the sample of A-share listed companies in Shanghai and Shenzhen during the twelfth five-year Plan period (2011–2015), this paper studies the impact of industrial policy and labor allocation on the innovation efficiency of enterprises to test the correlation among government policy, labor allocation and innovation efficiency. The empirical results show that industrial policy significantly improves the innovation efficiency of enterprises; at enterprises with low labor allocation, the innovation efficiency of enterprises is higher with an industrial policy. This study provides a new perspective and empirical evidence that government decision-makers can use in dealing with the relationship between government policies, labor market factors and enterprise innovation.
Syphilis in Pregnancy.

Importance Since 2013, the United States has seen a rise in cases of congenital syphilis, culminating in a relative increase of 153% from 2013 to 2017 and 918 reported cases in 2017. In all, 50% to 80% of pregnant women with syphilis experience an adverse pregnancy outcome including stillbirth or spontaneous abortion. Objective This article aims to review the current evidence and recommendations for management of syphilis in pregnancy. Evidence Acquisition Original research articles, review articles, and guidelines on syphilis were reviewed. Results In pregnancy, routine screening for syphilis is recommended on initiation of prenatal care. In high-risk populations, repeat testing is recommended in the early third trimester and at delivery. Penicillin remains the recommended treatment in pregnancy. After treatment, nontreponemal titers should be repeated at minimum during the early third trimester and at delivery to assess for serologic response. In high-risk populations, titers should be repeated monthly. Conclusion and Relevance Routine screening in pregnancy is essential for identification of syphilis infection and prevention of congenital syphilis. Subsequent adequate treatment with penicillin therapy more than 30 days before delivery and at the correct dosages depending on the stage of infection should be incorporated into clinical practice.
Does Corporate Governance Influence Voluntary Disclosure? Evidence from India

The purpose of this study is to examine the influence of different corporate governance (CG) attributes on voluntary disclosures (VD) made by 100 companies listed on the Bombay Stock Exchange (BSE) in their annual reports. To this end, the paper uses appropriate panel data regression technique, whereby the results indicate that three CG attributes—board independence, board gender diversity, and its risk management committee—have significant influence on VD. In particular, board independence is found to have weak negative influence on VD while its gender diversity and risk management committee indicate strong positive influence on VD. The other CG attributes, specifically the board size, role duality, ownership concentration, audit committee independence, and nomination and remuneration committees, do not reveal any significant influence on VD. Overall, the finding suggests that one of the conventional attributes of CG, i.e. board independence, acts with VD as an alternate control mechanism to reduce agency costs and protect investor interests. Meanwhile, VD co-exists with some of the latest CG attributes, including board gender diversity and its risk management committee, to monitor managers. The results of this paper should be relevant to regulators, practitioners, and other market participants in the Indian context, as well as other emerging markets with similar institutional settings.
Creativity Promotion in an Excellence Program for Preservice Teacher Candidates

Teacher education is a leading issue in education research, and creativity has been targeted as an important goal in teacher education. This study investigated little-c creativity in first-year preservice teacher candidates, as manifested in their yearlong fieldwork. It was designed as a qualitative empirical study. Three major themes related to the candidates’ creativity and the components that fostered it were revealed. The first was the process the candidates underwent to construct and implement their initiatives; the second was related to the process that the candidates underwent as they transitioned from feelings of chaos to creativity; and the third was the candidates’ interpersonal relationships. We conclude that preservice teacher education should provide unique experiences that foster creativity.
Financial forecasting using machine learning

Accurate predictions of the direction of the returns on stock/index are of paramount interest to market dealers and investors. Researchers have shown signiﬁcant interest in developing diﬀerent techniques to help generate high forecasting accuracy of stock returns or prices movement. In this essay, ﬁve diﬀerent techniques are considered and applied to predict the movement of the daily returns on the Standard and Poor 500 stock index (S&P 500). These techniques are Artiﬁcial Neural Network (ANN), Logit model, Linear Discriminant Analysis (LDA), Quadratic Discriminant Analysis (QDA) and K-Nearest Neighbour-hood classiﬁcation (KNN). Results show that ANN performed relatively better in the classiﬁcations of the up and down movements of the returns than the other techniques. Speciﬁcally, ANN achieved approximately 61 percent in predicting the returns using opening prices of stocks/indices.
Cryoablation for simultaneous surgical treatment of atrial fibrillation and valvular or ischemic heart diseases â€“ our early experience in Varna

Atrial fibrillation (AF) is a problem with rising frequencyÂ and importance in developed countries. The consequencesÂ of that condition are a significant medical, social and economicÂ problems: high risk of development of heart failure,Â ischemic stroke, decreased quality of life and lowered lifeÂ expectancy. With the development of theoretical knowledge and technical means in medicine, new surgical methods have been established and validated for the treatmentÂ of AF, among them is cryoablation. We present our earlyÂ experience with the concomitant treatment of AF withÂ cryoablation for patients undergoing surgical treatment ofÂ coronary artery disease (CAD), mitral and aortic valvularÂ pathology. The system used for cryoalbation uses nitrousÂ oxide (N2O). The results from patient follow-up show high effectiveness of the procedure even in the initial phase ofÂ mastering the skill.
Employee engagement, organisational commitment, and job satisfaction in Namibia, South Africa, and Zimbabwe: An exploratory study

The goal of this study was to measure employee engagement (EE), organisational commitment (OC), and job satisfaction (JS) in Namibia, South Africa, and Zimbabwe. We surveyed a convenience sample of 631 employees (South Africa: n = 219; Namibia: n = 212; and Zimbabwe: n = 200). The employees completed a selection of items from the Employee Engagement Scale, the Organisational Commitment Scale, and the Job Satisfaction Scale. Following analysis of variance and t-tests, results t-tests showed between-country differences in EE, OC, and JS in which South African employees reported higher scores than those from Namibia and Zimbabwe. Macro-level economic factors may explain the country differences in EE, OC, and JS.
Fast and reliable storage using a 5  bit, nonvolatile photonic memory cell

Optically storing and addressing data on photonic chips is of particular interest as such capability would eliminate optoelectronic conversion losses in data centers. It would also enable on-chip non-von Neumann photonic computing by allowing multinary data storage with high fidelity. Here, we demonstrate such an optically addressed, multilevel memory capable of storing up to 34 nonvolatile reliable and repeatable levels (over 5 bits) using the phase change material Ge2Sb2Te5 integrated on a photonic waveguide. Crucially, we demonstrate for the first time, to the best of our knowledge, a technique that allows us to program the device with a single pulse regardless of the previous state of the material, providing an order of magnitude improvement over previous demonstrations in terms of both time and energy consumption. We also investigate the influence of write-and-erase pulse parameters on the single-pulse recrystallization, amorphization, and readout error in our multilevel memory, thus tailoring pulse properties for optimum performance. Our work represents a significant step in the development of photonic memories and their potential for novel integrated photonic applications.
New Statistics of the Second-Order Chirp Cyclostationary Signals: Definitions, Properties and Applications

The chirp-cyclostationary (CCS) process is the generalized form of the cyclostationary (CS) process and it can describe the nonstationary stochastic signal models more exactly in practical applications. Basically, the statistics of the CCS signals have been defined and studied based on the correlation function. However, when the measurement is chosen as the above defined statistics, the output of a linear-variant filter is a zero-power signal for any input pure CCS signal. This is a barrier to further analyze the properties of the filters by the second-order statistics. In this paper, firstly two new complementary correlation function-based statistics and their basic properties are proposed and discussed. These two new statistics are connected by the generalized cyclic Wiener-Khinchin theorem. Then, we examine that the output of the filter is non-zero power under these new measurements. Based on this, the theories about the matched filter and system identification are developed, whose advantages are analyzed in theory. Finally, by proposing the estimators to the two statistics via a single record, the advantages of the proposed statistics over the classical second-order statistics are examined by the communication signals and the electrocardiogram (ECG) signals.
Collaborative Art: A Transformational Force within Communities

This article provides a new perspective on collaborative art as a transformational force to strengthen community and enhance well-being. We outline a best practices-based framework to foster community-based, collaborative art such as cocreated community murals. Specifically, we identify a strategic and successive process for collaborative art initiatives by integrating the academic literature on art, aesthetics, community, and consumer research together with the practices of arts organizations working to transform communities through participatory, cocreated art. The article highlights the contributions of this work to academic research, public policy, and community organizing efforts and outlines questions to encourage more researchers and practitioners to investigate the dynamics of collaborative art to transform communities.
Joint Transceiver Optimization for Wireless Communication PHY with Convolutional Neural Network

Deep Learning has a wide application in the area of natural language processing and image processing due to its strong ability of generalization. In this paper, we propose a novel neural network structure for jointly optimizing the transmitter and receiver in communication physical layer under fading channels. We build up a convolutional autoencoder to simultaneously conduct the role of modulation, equalization and demodulation. The proposed system is able to design different mapping scheme from input bit sequences of arbitrary length to constellation symbols according to different channel environments. The simulation results show that the performance of neural network based system is superior to traditional modulation and equalization methods in terms of time complexity and bit error rate (BER) under fading channels. The proposed system can also be combined with other coding techniques to further improve the performance. Furthermore, the proposed system network is more robust to channel variation than traditional communication methods.
Affective Behaviour Analysis of On-line User Interactions: Are On-line Support Groups More Therapeutic than Twitter?

The increase in the prevalence of mental health problems has coincided with a growing popularity of health related social networking sites. Regardless of their therapeutic potential, on-line support groups (OSGs) can also have negative effects on patients. In this work we propose a novel methodology to automatically verify the presence of therapeutic factors in social networking websites by using Natural Language Processing (NLP) techniques. The methodology is evaluated on on-line asynchronous multi-party conversations collected from an OSG and Twitter. The results of the analysis indicate that therapeutic factors occur more frequently in OSG conversations than in Twitter conversations. Moreover, the analysis of OSG conversations reveals that the users of that platform are supportive, and interactions are likely to lead to the improvement of their emotional state. We believe that our method provides a stepping stone towards automatic analysis of emotional states of users of online platforms. Possible applications of the method include provision of guidelines that highlight potential implications of using such platforms on users’ mental health, and/or support in the analysis of their impact on specific individuals.
Revisiting Hearing the Other Side : Distinct Associations of Social Network Characteristics With Political Discussion and Participation

This study extends research on the impact of cross-cutting political discussion on dialogic openness and political participation by considering political network diversity and network sizes of various tie strengths. The study employs a national survey of U.S. citizens ( N = 1,001) and finds distinct paths to political participation through political networks’ attributes and political discussions according to network type and size. The study also identifies an interaction between cross-cutting discussion and strong tie political homogeneity on both dialogic openness and political participation. Politically homogeneous strong ties dampen participation when unaccompanied by frequent cross-cutting discussion. The study’s findings contribute to conceptual and empirical distinctions between the sizes of general social networks and the attributes of political networks. The research integrates various theorizations of the process leading to political participation.
Fault Prediction of a Transformer Bushing Based on Entropy Weight TOPSIS and Gray Theory

Transformer bushing insulation fault prediction can effectively guide transformer maintenance. The fault prediction method of a transformer bushing based on entropy weight TOPSIS and gray prediction theory is studied. This method uses the entropy theory instead of the subjective experience to determine the weight of the evaluation indicator. The TOPSIS evaluation method is used to transform the insulation evaluation problem into the vector space distance problem. Based on the Euclidean distance between the test data and standard grade data, the assessment problem is transformed into a distance problem of vector space. The state of a transformer bushing can be obtained from the TOPSIS calculations. Subsequently, the development trend of the fault state is predicted by using the insulation state data and the gray GM (1.1) prediction model. Prediction results are helpful for maintenance. The validity of the method was verified by the example.
Risk and Protective Factors for Peer Victimization in Adolescents with ADHD

ABSTRACT Youth with ADHD are more at-risk for peer victimization than their typically developing peers, and may not be benefiting from current interventions. Thus, we sought to examine risk (i.e., anxiety, depression, and forms of aggression) and protective (i.e., social skills and social acceptance) factors for peer victimization in this group. Participants were 123 young adolescents diagnosed with ADHD, who were attending grades six through eight. We found that relational aggression (i.e., excluding others from activities) and anxiety symptoms were among the strongest risk factors for victimization. Anxiety symptoms were associated with victimization over and above depressive symptoms. Social acceptance buffered risk conferred by the risk factors. Future work is needed to investigate the degree to which the relations among internalizing symptoms and victimization differ in youth with ADHD relative to typically developing youth, and assess causality of the relations.
Innovation Strategy, Market Orientation and Competitive Advantage Influence on the Performance of SMEs Company in SMESCO Indonesia

This study analyzed 147 SMEs company owners in SMESCO Indonesia with structural model equation modeling-partial least squares (SEM-PLS) tool. Method of sampling non probability sampling with purposive sampling. The result of the research: firstly that innovation strategy has no effect on the performance of SMEs company (positively insignificant), but positively influential to the performance of SMEs company through competitive advantage; secondly that market orientation has no effect on company performance (negative not significant), but positively significant effect of market orientation on company performance through competitive advantage.