Miracle-dz/UniFAR-FTUs huggingface dataset:
Improving Core Topics Discovery in Semantic Markup Literature: A Combined Approach

This research configures a corpus of articles related to the aspects being investigated in Semantic Markup, knowledge domain that has evolved and expanded over the last decade and conduct a manual process to identify the Topics being addressed. Then, it is used LDA, an unsupervised probabilistic topic model, and other tools, for automatically recognize the topics of interest within this corpus; this aims to interpret, validate and complement the results manually obtained. The results let us argue that using combined techniques contribute to improving the human expert analysis, and it is helpfully for the discovery of core topics in Semantic Markup Literature.
Cost-Effective Edge Server Placement in Edge Computing

In a smart city powered by the 5G network, a large amount of data never seen before will be generated. The conventional cloud computing paradigm cannot fulfil users' needs, especially for low latency. The new edge computing paradigm is emerging to mitigate the this problem. There has been some prominent research results in the field of edge computing, but most of the work is based on the assumption that edge servers have been deployed at ideal locations, and little attention has been paid to how edge servers are deployed in a geographic area. In this paper, we study how to deploy edge servers cost-effectively so that the collective area of edge servers is maximized under a certain deployment budget. In addition, there are two issues to consider in the deployment of edge servers. The first is the deployment cost, and the second is the area covered by those edge servers. For the first issue, a dynamic programming algorithm is proposed to find a solution. The key idea is to find the maximum area under a given cost. For the second issue, the geometric image approach is used to calculate the area covered by the edge server. The results of the experiments conducted on a real-world dataset demonstrate, our method is superior to several representative methods in terms of coverage maximization and running time.
Does Trait Loneliness Predict Rejection of Social Robots? The Role of Reduced Attributions of Unique Humanness : Exploring the Effects of Trait Loneliness on Anthropomorphism and Acceptance of Social Robots

Since chronic loneliness is both a painful individual experience and an increasingly serious social problem, robot companions have emerged as a result of robotization of social work to confront this issue. We foresee that social robots will become pervasive in the near future. Thus, it is crucial to pinpoint the relationship between chronic experiences of loneliness (i.e., trait loneliness) and both anthropomorphism and acceptance of such artificial intelligent agents. Previous research demonstrated that experimentally induced state loneliness increases anthropomorphic inferences about nonhuman agents such as pets. However, in the present research we found that trait (vs. state) loneliness — a permanent personality disposition that is not easily relieved (vs. transitory experiences caused by circumstance, and easily relieved) — reduced participants’ anthropomorphic tendencies and acceptance of a social robot (regardless of the form: a picture of the robot, an on-site robot, or direct interaction with the robot). In particular, believing that the robot lacks good “unique humanness” traits (i.e., Humble, Thorough, Organized, Broadminded, and Polite) is one reason why dispositionally lonely participants are less likely to anthropomorphize a robot, which further prompts reduced acceptance of it. This finding suggests that unique humanness, exemplifying secondary emotions, is vital, not only in interpersonal contexts, but in establishing connections with social robots. ACM Reference format: Sijia Li, Liying Xu, Feng Yu & Kaiping Peng. 2020. Trait Loneliness Predict Rejection of Social Robots? The Role of Reduced Attribution of Unique Humanness: Exploring the Effects of Trait Loneliness on Anthropomorphism and Acceptance of Social Robots. In Proceedings of 2020 ACM Human Robot Interaction (HRI’20), March 23-26, 2020, Cambridge, UK. ACM, NY, NY, USA. 8 pages. https://doi.org/10.1145/3319502.3374777
Keep Calm and Code on Your Phone: A Pilot of SuaCode, an Online Smartphone-Based Coding Course

Africa lags behind the rest of the world in terms of digital literacy skills with less than one percent of African children leaving school with basic coding skills. One cause of this gap is poor access to equipment such as computers for teaching and learning. Yet, there is a proliferation of smartphones in Africa. Seeking to leverage this opportunity, we developed SuaCode, an online smartphone-based coding course to teach programming fundamentals to Africans. We designed the course to teach coding in a visual, interactive and fun way through the building of a pong game using Processing (a Java-based programming language). In this work, we describe our experience delivering the course online to 30 Ghanaian high school and college students. At the end of the course, 7 of the 30 students completed the first part of the course, building the pong game. The reflection essays from our students showed that they enjoyed the course and coding on a smartphone was not a barrier to completing the assignments. Improvements such as having more mentors and automated feedback on the coding assignments will improve the quality of the course. Given the difficulty in accessing computers in Africa, our work shows that smartphones can be leveraged to effectively introduce students to programming concepts via an online course. We are excited about the results of this pilot and see the potential to scale the course to eventually bring coding skills within arm's reach of millions across Africa, literally into their palms thereby bridging Africa's digital divide.
An Efficient Approach to Generating Cryptographic Keys from Face and Iris Biometrics Fused at the Feature Level

Biometrics, defined as automated recognition of individuals based on their behavioral and biological characteristics, is beginning to gain acceptance as a legitimate authentication method and a practicable option to traditional identification methods in several application areas. Biometric cryptosystems, designed to generate a cryptographic key from a biometric trait, incorporate high level of security provided by cryptography and non-repudiation provided by biometry, as well as eliminating the need for a user to remember long passwords or carry tokens. Unlike unimodal biometric systems that employ single feature, multimodal biometric cryptosystems generate keys from two or more individual modalities typically fused at feature level. Fusing feature sets related to different modalities prevents possible spoof attacks and provides the system with higher level of overall security. This paper present an efficient approach to secure cryptographic key generation from iris and face biometric traits. Features extracted from preprocessed face and iris images are fused at the feature level and the multimodal biometric template is constructed from the Gabor filter and Principal Component Analysis outputs. This template is used to generate strong 256-bit cryptographic key. Experiments were performed using iris and face images from CASIA and ORL databases and the efficiency of the proposed approach is confirmed.
Double primary carcinoma of endometrial carcinoma and colorec- tal carcinoma: retrospective analysis of 34 cases and discussion of its relationship with Lynch syndrome

2 Pe- king Union Medical College, Beijing 100021, China Abstract Objective: To approach the clinicopathologic characteristics, treatment modalities, and prognosis of the patients with double primary carcinoma of endometrial carcinoma and colorectal carcinoma and analyze the relationship between this disease and Lynch syndrome. Methods: The clinicopathologic and follow-up data of 34 cases with double primary carcinoma of endometrial carci- noma and colorectal carcinoma treated in Cancer Hospital of Chinese Academy of Medical Sciences were reviewed. Results: The medi- an age of the 34 patients was 51.5 years old (ranging from 39 to 76). Twenty-two of the total cases (22/34, 64.7%) had tumor family his- tory. The pathologic results indicated that 79.4% (27/34) was endometrioid adenocarcinoma. In the 34 cases, 33 were treated by surgical procedure. Of the 33 cases undergoing surgery, 17 patients with endometrial carcinoma and 19 with colorectal carcinoma received fur- ther adjuvant treatment of chemotherapy and /or radiotherapy. The 2- and 5-year survival rates were 84.3% and 63.1% in the 34 cases, respectively. Conclusion: The age of onset is earlier in the patients with double primary carcinoma than in those with sporadic colorec- tal carcinoma. Some cases have cancer family history, and their survival rates are similar to those of the patients with sporadic colorec-
The Effect of Patient Scheduling in a Gastrointestinal Clinic using Simulation.

MCNEAL, KATHRYN ELIZABETH. The Effect of Patient Scheduling in a Gastrointestinal Clinic using Simulation (Under the direction of Javad Taheri). The problem of determining an optimal scheduling method for multi-phase outpatient clinics where patients need an array of doctors and nurses throughout the appointment is complex. The goal of this thesis is to establish a scheduling rule to maximize the number of patients that can be seen each day at the Durham VA GI Clinic while maintaining acceptable levels of doctor overtime and patient waiting time. Different appointment scheduling rules are generated that combine sequencing of patients and the number of patients in each interval. A discrete event simulation was created using data from the Durham VA GI Clinic, and was used to evaluate the scheduling rules. Schedules with the same total number of patients were compared to determine which one has the lowest objective value, the weighted average of doctor overtime and patient waiting time, for given sets of weights. The best scenarios for each total number of patients between 28 and 36 were analyzed to look for common scheduling rules that work well in all scenarios for each set of weights. A “best” scheduling rule was selected for each set of weights, and the average objective value was found for each number of patients using that rule. By comparing this to the simulation results of the current schedule, the maximum number of patients the clinic should select can be determined based on how much of an increase in average overtime and patient waiting
Weak Sparsity Adaptive Matching Pursuit Algorithm based on Environmental Monitoring Sensor Network Data

Due to the undetermined signal sparsity in environmental monitoring applications, the compressed sensing reconstruction algorithm with sparsity adaptive characteristics has better application value. In order to improve the reconstruction accuracy of the reconstruction algorithm, this paper proposes a weak sparsity adaptive matching pursuit algorithm. Firstly, the algorithm constructs the candidate set by weak selection, and then introduces the backtracking idea to filter the candidate set atoms and form a support set. In addition, the algorithm applies the idea of variable step size, and selects different step sizes for different iterations to achieve more accurate and complete reconstruction. Simulation experiments show that the improved algorithm proposed in this paper has higher reconstruction accuracy than similar algorithms.
In Storage, Yet on Display : An Empirical Investigation of Robots’ Value as Social Signals

This paper suggests that humans value robotic systems as signals – costly, visible commitments that can secure access to preferred resources. This contrasts with HRI research, design, engineering and deployment, which have focused on robots’ instrumental value – namely how designing and interacting with them may produce more or less productivity. Drawing on a multiyear ethnography of a “failed” robotic telepresence deployment in a teaching hospital, this paper shows that robots’ signaling value can significantly outweigh – and even contravene – any practical utility that they may provide through use. This analysis further suggests that – unlike nontechnological organizational signals – robots’ signaling value is highly contingent on the observability of their use. Considering robots’ signaling value in complex social systems such as organizations promises improved robotic systems development and deployment techniques and improved prediction regarding human-robot interaction. CCS CONCEPTS • HRI theory, concepts and models • Ethnographic studies • Empirical studies in HRI Acm Reference Format: Matthew I. Beane. 2020. In Storage, Yet on Display: An Empirical Investigation of Robots’ Value as Social Signals. In Proceedings of 2020 ACM/IEEE International Conference on Human-Robot Interaction (HRI’20), March 23–26, 2020, Cambridge, United Kingdom. ACM, New York, NY, USA, 9 pages. https://doi.org/10.1145/3319502.3374775
Not Some Random Agent: Multi-person Interaction with a Personalizing Service Robot

Service robots often perform their main functions in public settings, interacting with more than one person at a time. How these robots should handle the afairs of individual users while also behaving appropriately when others are present is an open question. One option is to design for flexible agent embodiment: letting agents take control of different robots as people move between contexts. Through structured User Enactments, we explored how agents embodied within a single robot might interact with multiple people. Participants interacted with a robot embodied by a singular service agent, agents that re-embody in different robots and devices, and agents that co-embody within the same robot. Findings reveal key insights about the promise of re-embodiment and co-embodiment as design paradigms as well as what people value during interactions with service robots that use personalization. CCS CONCEPTS •Human-centered computing → Laboratory experiments. Acm Reference Format: Samantha Reig, Michal Luria, Janet Z Wang, Danielle Oltman, Elizabeth Jeanne Carter, Aaron Steinfeld, Jodi Forlizzi, and John Zimmerman. 2020. Not Some Random Agent: Multi-person Interaction with a Personalizing Service Robot. In Proceedings of the 2020 ACM/IEEE International Conference on Human-Robot Interaction (HRI ’20), March 23-26, 2020, Cambridge, United Kingdom. ACM, New York, NY, USA, 9 pages. https://doi.org/10.1145/3319502.3374795
Association of metabolic NCD risk factors with oral, breast and cervical precancers and cancers in India

Objective To find an association between metabolic non-communicable disease (NCD) risk factors (high blood pressure (BP), high random blood sugar (RBS) and overweight /obesity) and oral, breast, cervical cancers/precancerous or potentially malignant conditions. Design This is an observational study using convenience sampling. The participants were screened through opportunistic or population-based screening. Setting The study was conducted at a health promotion clinic (HPC) located in Northern India under the Indian Council of Medical Research. HPC is a screening clinic where screening is done for hypertension (HT), diabetes mellitus (DM), obesity, and oral, breast and cervical cancers. The study was conducted between December 2016 and January 2019. Participant The number of participants screened was 8352 (6712 women and 1640 men). All consenting men and women above 18 years were included. All participants were screened for oral cancer, DM, HT and obesity. All women were also screened for breast and cervical cancers. Cervical screening was done for non-pregnant women 21 years and above with history of sexual activity. Result Oral potentially malignant disease (OPMD) was the most prevalent, followed by breast cancer, oral cancer, cervical cancer and cervical precancer. High RBS had a strong association with oral cancer (OR=2.29, 95% CI 1.09 to 4.82, p=0.03) and breast cancer (OR=1.95, 95% CI 1.01 to 3.76, p=0.05). High BP had a strong association with breast cancer (OR=2.50, 95% CI 1.43 to 4.35, p<0.0001). An inverse association was noted between oral cancer and overweight/obesity (OR=0.20, 95% CI 0.08 to 0.48, p<0.0001). Current tobacco use was strongly associated with oral cancer (OR=6.51, 95% CI 3.63 to 11.67, p<0.0001) and OPMD (OR=9.82, 95% CI 8.13 to 11.86, p<0.0001). No association was elicited between the metabolic NCD risk factors and cervical cancer/precancer. Conclusions The study reaffirms that NCD metabolic risk factors determine oral and breast cancers. Besides NCD risk factors, current tobacco use was a strong determinant of OPMD and oral cancer. Hence, primary and primordial prevention measures to control NCD metabolic risk factors and tobacco use should move along with secondary prevention of breast and oral cancers.
An Efficient Software Fault Prediction Scheme to Assure Qualified Software Implementation using Improved Classification Methods

: Software quality is a main concern of software developers to ensure the required software that can provide user required services. However quality of software would be degraded considerably due to presence of the software faults in the programming language. Detection and removal of software faults requires more concern to be taken which needs to be concentrated more for improved performance. In the existing research work, accurate software fault prediction is done by introducing two stage data pre-processing stage which would select the more important features from the training data set and will result with the optimal training dataset thus the training accuracy can be improved. However existing research method doesn’t concentrate the dependencies between software modules and it doesn’t focus on the classification performance. These challenges are highlighted in the newly introduced research methodologies to obtain the accurate software prediction outcome by introducing the novel proposed research methodology namely Optimal and eliable Prediction of Software Faults (ORPSF). In the proposed research methodology, Optimal feature selection is performed by considering the inter relationship between the different features using Genetic Algorithm. This technique would select the optimal features which can detect the software faults accurately than the existing research methods. And the SVM classification approach is introduced to perform classification which can learn the training instances more accurately. Thus software fault prediction can be done accurately. The overall implementation of the proposed research technique is performed in the java simulation environment from which it can be shown that the proposed research methodology yields optimal results compared to the available research techniques.
TRANSACTION PROCESSING IN MOBILE DEVICES

- The innovation in mobile technology and wireless network enhance the use of mobile device in database driven application. These applications require high reliability and availability. The innovation, combined with accessibility of sophisticated mobile device facilitating anywhere, at whatever time access, have made versatile applications an extremely basic component. Authorization of information respectability and treatment of concurrency and exchange disappointment has turn out to be more amplified because of nature being remote and information being continuous. In this paper we have made complete review of the effects of mobile environment on transaction management and useful work done in mobile transaction. We also focus on review lot of proposed model of mobile transaction which used to enhance transaction processing.
BRAIN COMPUTER INTERFACE APPLICATION IN STROKE DISEASE DIAGNOSIS

Every discovery is geared towards problem solving. This is manifested by the advent of brain computer interface (BCI). Brain computer interface (BCI) is a field of study concern with the detection and utilization of brain signals in establishing the communication path between the brain and the computer system. The knowledge of this science has helped in no small measure in providing solutions to several challenges befalling man and his environment. In this paper, we explored those areas where BCI has proved useful and pointed out as well its possible application in diagnosis of stroke disease. The discourse was centered on detection of electrochemical signals from the brain called electroencephalogram (EEG). The research work also highlighted the technique of recording brain activity via electroencephalogram and using it in making deduction on the status of stroke attack on individual. This can either be normal or abnormal. The presence of delta or theta wave in an awaked adult suggests an abnormal situation. While the observance of alpha, beta and gamma waves are interpreted as normal.
Dynamic Tone Mapping Operator for Maximizing Tone Mapped Image Quality Index

The use of photography and the application of the resultant picture has become vital in such a way that the picture should express all the information present in the environment. This is not possible unless Tone Mapping Operators (TMOs) are used. It converts the High Dynamic Range (HDR) image into an equivalent Low Dynamic Range (LDR) image with as much information possible. The method used to measure the quality of the Tone Mapping Operator is mostly subjective thereby an optimization framework is not possible. Here an objective evaluation technique is used which takes both Structural Fidelity as well as Statistical Naturalness measure. The results are verified by cross checking against the Subjective Evaluation scores. It is attached as an optimization framework to Gamma Tone Mapping operator to obtain the maximum possible quality obtainable from these tone mapping operator.
Synthesis of Nanoparticles of Titanium Dioxide TiO2 for Toxicological Studies: A Short Review

Nanoparticles have unique properties relative to the large particles, allowing their use in many nanomaterials. For example, TiO2 nanoparticles are widely used in cosmetics, paints and foodstuffs for their various properties, including colloidal stability, high reflection index and photo catalytic properties [1]. However, several toxicological studies have shown that nanoparticles can be potentially hazardous because of these unique physicochemical properties [2-4]. In particular, the very large specific surface area of nanomaterials greatly increases their surface reactivity with biological media.
An efficient method for classification of rice grains using Morphological process

-The Agricultural industry is too oldest and most widespread industry in the world. Quality evaluation of grains is a very big challenge since time immemorial. The paper presents an automatic evaluation method for determination of quality of milled rice. Among the milled rice samples the quality of broken rice kernels are determined with the help of shape descriptors and geometric features. Grains are said to be broken kernels whose lengths are 75% of the grain size. This method gives good results in evaluation of rice quality.
OCCURRENCE AND CLINICOLABORATORY PROFILE OF MYCOPLASMA INFECTION IN CHILDREN HOSPITALIZED WITH LOWER RESPIRATORY TRACT INFECTION – A PROSPECTIVE STUDY

Hareesh Vardhan Jadala1, Raghavendra K2 From 1Post Graduate, 2Associate Professor, Department of Paediatrics, Basaveshwara Medical College Hospital and Research Centre, Chitradurga, Karnataka, India Correspondence to: Dr. Raghavendra K, Department of Paediatrics, Basaveshwara Medical College Hospital, Chitradurga 577 501, Karnataka, India. E-mail: anaghawatson@gmail.com Received 14 October 2019 Initial Review 01 November 2019 Accepted 08 November 2019