bluuebunny/crossref_metadata_2025 huggingface dataset:
MTBalance
Authors: Berentsen Mark J. , Bentvelzen Marit , Woźniak Paweł W.
Published: November 2021

Mountain Biking (MTB) is an increasingly popular outdoors activity which offers a unqiue connection to nature along with the health benefits of cardiovascular exercise. Yet, complex MTB technique is an entry barrier that often prevent novices from enjoying the sport. Developing interactive systems, which can support developing MTB proficiency can augment the outdoor experience and make the sport available to a larger group of users. To that end, we designed, implemented and evaluate MTBalance - a system which provides body posture feedback for beginner mountain bikers. Based on inertial tracking, MTBalance informs the user about how to correct their posture to improve MTB performance. We conducted a study in which we compared different feedback modalities for MTBalance. We observed that the system increased perceived balance awareness. Our work provides insights for designing body awareness systems for outdoor sports.
Traces of Time through Space
Authors: Kirshenbaum Nurit , Davidson Kylie , Harden Jesse , North Chris , Kobayashi Dylan , Theriot Ryan , Tabalba Roderick S. , Rogers Michael L. , Belcaid Mahdi , Burks Andrew T. , Bharadwaj Krishna N. , Renambot Luc , Johnson Andrew E. , Long Lance , Leigh Jason
Published: November 2021

Technology have long been a partner of workplace meeting facilitation. The recent outbreak of COVID-19 and the cautionary measures to reduce its spread have made it more prevalent than ever before in the form of online-meetings. In this paper, we recount our experiences during weekly meetings in three modalities: using SAGE2 - a collaborative sharing software designed for large displays - for co-located meetings, using a conventional projector for co-located meetings, and using the Zoom video-conferencing tool for distributed meetings. We view these meetings through the lens of effective meeting attributes and share ethnographic observations and attitudinal survey conducted in our research lab. We discuss patterns of content sharing, either sequential, parallel, or semi-parallel, and the potential advantages of creating complex canvases of content. We see how the SAGE2 tool affords parallel content sharing to create complex canvases, which represent queues of ideas and contributions (past, present, and future) using the space on a large display to suggest the progression of time through the meeting.
Review of Communication Complexity and Applications by Anup Rao and Amir Yehudayoff
Authors: Cadilhac Michael
Published: November 2021

At its core, communication complexity is the study of the amount of information two parties need to exchange in order to compute a function. For instance, Alice receives a string of characters, Bob receives another, and they should decide whether these strings are the same with as few rounds of communication as possible. Multiple settings are conceivable, for instance with multiple parties or with randomness. Upper and lower bounds for communication problems rely on a wealth of mathematical tools, from probability theory to Ramsey theory, making this a complete and exciting topic. Further, communication complexity finds applications in different aspects of theoretical computer science, including circuit complexity and data structures. This usually requires to take a "communication" view of a problem, which in itself can be an eye-opening vantage point.
Preserved β-adrenergic-mediated vasodilation in skeletal muscle of young adults with obesity despite shifts in cyclooxygenase and nitric oxide synthase
Authors: Limberg Jacqueline K. , Johansson Rebecca E. , Carter Katrina J. , Peltonen Garrett L. , Harrell John W. , Kellawan J. Mikhail , Eldridge Marlowe W. , Sebranek Joshua J. , Walker Benjamin J. , Schrage William G.
Published: November 2021

We examined β-adrenergic receptor-mediated vasodilation in skeletal muscle of normal weight and humans with obesity. Results show that despite shifts in the contribution of cyclooxygenase and nitric oxide synthase, β-adrenergic-mediated vasodilation is relatively preserved in young, otherwise healthy adults with obesity. These data highlight the presence of subclinical changes in microvascular control mechanisms early in the obesity process and suggest duration of obesity and/or the addition of primary aging may be necessary for overt dysfunction.
Analysis of Subgradient Extragradient Iterative Schemes for Variational Inequalities
Authors: Wu Danfeng , Zhu Li-Jun , Shan Zhuang , Yin Tzu-Chien
Published: November 2021

In this paper, we investigate the monotone variational inequality in Hilbert spaces. Based on Censor’s subgradient extragradient method, we propose two modified subgradient extragradient algorithms with self-adaptive and inertial techniques for finding the solution of the monotone variational inequality in real Hilbert spaces. Strong convergence analysis of the proposed algorithms have been obtained under some mild conditions.
Geological Modeling Technology and Application Based on Seismic Interpretation Results under the Background of Artificial Intelligence
Authors: Peng Ximing , Li Minglu , Zhu Yalin , Li Na , Dong Hao
Published: November 2021

The development of seismic technology has made seismic data to be widely used in the interpretation of stratigraphic sequence frames, reservoir identification, fluid detection, and other research fields involved in reservoir description. The 3D technology reservoirs have always been the focus, as well as difficulty, of research. With the rapid development of information technology and the continuous improvement of seismic exploration level, people have put forward higher requirements for the accuracy of seismic data interpretation results. Aiming at the large number of structural and unstructured data in seismic, logging, geology, and other disciplines involved in seismic interpretation, how to effectively organize and coordinate analysis to discover the hidden reservoir structure and oil and gas distribution information has always been a geological and important topic for information processing technicians. This thesis is aimed at the current high-water-phase development of Shengtuo Oilfield reservoir and the problems existing in geological research. Based on seismic structural interpretation and attribute analysis, this paper analyzes the reservoir structural characteristics, sedimentary characteristics, and reservoir physical parameter characteristics based on geology, logging interpretation, core analysis, drilling, and seismic interpretation. Using the kriging method with external drift can cooperate with seismic variables to establish a reservoir geological model to study the Shengtuo Oilfield reservoir. We combine artificial intelligence technology with geological modeling technology of seismic interpretation results to explore the best method for predicting earthquakes. The research results in this paper show that the relative error of the model established by the kriging method in the article is relatively small for thinning wells, mainly concentrated around 1%. Examination of the thinning wells of 45 wells shows that the model established is basically good and the example has high accuracy. The research results in this paper have a guiding study of distribution and tapping potentials in the study area, formulating reasonable development and adjustment plans and improving oil recovery.
Stability Analysis of Ecological Slopes Based on a 3D Finite Element Model
Authors: Sui ZiFan , Yuan Weijia , Yi Wen , Yang Weihuan
Published: November 2021

To explore the effect of grass and shrub plant roots on the stability of soil slopes in rainy areas in the south, this article relies on the Longlang Expressway construction project. Cynodon dactylon and Magnolia multiflora were selected as research subjects. The plant distribution characteristics and mechanical properties are analyzed. This paper uses ABAQUS finite element software to construct a 3D model of the planted slope in the test section. The stress and strain on the root system and the soil were observed, and the variation law of slope stability before and after plant protection under different rainfall events was compared and analyzed. The test and simulation results show that the root content of Cynodon dactylon gradually decreases with increasing depth. Cynodon dactylon was mainly distributed in the 0–30 cm soil body, and its effect on improving the cohesion of the soil body reached 75%. Magnolia multiflora belongs to vertical roots and has a strong and longer main root with relatively developed lateral roots. Its root system passes through the sliding surface of the slope bottom, which reduces the maximum equivalent plastic stress generated inside the slope by 61%. When the total rainfall duration is unchanged, under the three rainfall intensities of small, medium, and large, herbaceous plants increase the safety factor of the soil by 1.33%, 2.08%, and 6.1%, respectively, and the roots of shrubs increase the safety factor of the soil by 3.29%, 4.08%, and 4.32%, respectively. When the rainfall intensity does not change, as the rainfall time increases, the effect of plants on the slope safety factor first gradually increases and eventually stabilizes. The research results provide a reliable theoretical basis for analyzing the effect of plant roots on soil consolidation and slope protection, and they also lay a technical foundation for the promotion and application of ecological slope protection technology.
The Construction of a Digital Resource Library of English for Higher Education Based on a Cloud Platform
Authors: Wang Jing , Li Wei
Published: November 2021

This paper conducts in-depth research and analysis on the construction of an English digital resource library for higher education through the cloud platform. The cloud platform allows the English resource library to achieve integration, efficiency, scalability, and interactivity and then solves the problems of how to realize the co-construction and sharing of resources among multiple platforms in vocational institutions and improve the utilization rate of resources. The construction of the English resource library in higher vocational institutions cannot be separated from the collaboration between institutions and enterprises, and institutions must face up to the problems existing in the construction of the current resource library. Firstly, the requirements of various aspects of the higher vocational English digital resource library system are given from three aspects, functional requirements, performance requirements, and operational requirements, in strict accordance with the requirement analysis steps; secondly, the overall technical architecture and network topology architecture of the education cloud platform where the higher vocational English digital resource library system is located are analyzed and given in general to ensure the security, scalability, and ease of operation of this platform and then the resource collection and resource storage. The application of cloud computing technology can solve the problems of difficulty in obtaining teaching resources, insufficient storage space, limited communication, and slow circulation; it can realize the integration and integrated management of various resources through technologies such as networking, virtualization, and distributed storage. Finally, based on the optimization strategies proposed in this paper, the core modules of the higher vocational English digital resource library system are designed and implemented, and some important and representative interfaces and source codes are demonstrated. To ensure the operation performance, the situation of multiple users operating the higher-level English digital resource library system at the same time is simulated, and the overall performance of the higher-level English digital resource library system is evaluated for the common operations such as uploading resource files, downloading resource files, and querying resource files, which confirms the rationality of the design strategy in this paper and greatly improves the user experience and increases the utilization rate of teaching resources.
High Expression of GSDMC Is Associated with Poor Survival in Kidney Clear Cell Cancer
Authors: Cui Yun-Qian , Meng Fei , Zhan Wen-Li , Dai Zhou-Tong , Liao Xinghua
Published: November 2021

This study is aimed at exploring the potential role of GSDMC in kidney renal clear cell carcinoma (KIRC). We analyzed the expression of GSDMC in 33 types of cancers in TCGA database. The results showed that the expression of GSDMC was upregulated in most cancers. We found a significant association between high expression of GSDMC and shortened patient overall survival, progression‐free survival, and disease‐specific survival. In vitro experiments have shown that the expression of GSDMC was significantly elevated in KIRC cell lines. Moreover, decreased expression of GSDMC was significantly associated with decreased cell proliferation. In summary, we believe that this study provides valuable data supporting future clinical treatment.
[Retracted] A Study on the Application of Music Education to Improve College Students’ Mental Health in the Context of 5G
Authors: Li Jiawen
Published: November 2021

This paper provides an in‐depth study and analysis of music education to improve the mental health of college students in the context of 5G and for practical application. How to explore the ideas and methods of using music education to channel and resolve the psychological problems of this student group and then help them shape a healthy and upward psychological state, based on field research on the psychological and emotional health of contemporary higher education students, becomes an important issue that needs to be solved in front of most music educators. Musical emotions are not only related to the acoustic properties of music but also closely related to the age, gender, musical background, and social cognition of individuals. To explore the neural mechanisms by which musical rhythm affects emotional processing, it is necessary not only to achieve reasonable manipulation of rhythmic variables but also to effectively control for relevant additional variables, to clarify the relationship between rhythm and musical emotion from a theoretical perspective, and to provide operational guidance significance for bringing into play the mental health value of musical emotion. Discuss the commonalities and mutual assistance between the interactional music classroom and humanistic and positive psychology in terms of ideological connotations. Discuss the practical implications of humanistic psychology and its derivation of positive psychology in terms of self‐actualization, student‐centered view of education, associated integration and developmental educational values, psychological fluency experience, positive emotions, positive self, and positive motivation, which have common ideas with the philosophical theory of interaction, for the interactive music classroom. The characteristics and role of the music teacher in the interacting music classroom from a psychological perspective are described in terms of both teacher psychological construction and teaching attitudes. The enrichment of the ideas, psychological laws, and experiences in humanistic and positive psychology on the model of the interacting music classroom guided by the philosophical theory of interaction is discussed, divided into four subsections: suggestions for classroom goal setting, suggestions for teaching methods, teacher‐student evaluation, and teaching fragment design, aimed at making teachers and students interact easily and happily and live soberly and creatively.
Healthcare Providers’ Intention to Use Technology to Attend to Clients in Cape Coast Teaching Hospital, Ghana
Authors: Boadu Richard Okyere , Lamptey Mary Adama , Boadu Kwame Adu Okyere , Adzakpah Godwin , Mensah Nathan Kumasenu
Published: November 2021

Background. Patient records’ relevance is associated with a variety of needs and objectives. Substantiating the health of patients perpetually and allowing professionals in the medical field to assess both signs and symptoms that fall in a relatively wider temporal point of view and contributions that lead to enhanced diagnoses and treatment are all quintessential of patient records. The advancement of information technology systems has led to the anticipation that development will be put into digitization and electronic means of storing patient records in order to grease their handling. Cape Coast Teaching Hospital (CCTH) is piloting implementation of patient’s electronic health record system. The introduction of the electronic health record system known as Lightwave Hospital Information Management System (LHIMS) was to provide a permanent solution to patients’ continuity of care. User’s acceptance of new information technology is seen to be one of the most challenging issues in information system. This study assesses healthcare providers’ (HP’) behavioural intention to use LHIMS to attend to clients in Cape Coast Teaching Hospital and other factors influencing it. Methods. A nonexperimental cross‐sectional study was used to obtain information from 84 HP recruited from the various departments and units in CCTH who use LHIMS to attend to clients. The sample size of 90, representing 8% of HP in CCTH, was randomly selected from the various departments and units. However, 84 (indicating 93.3% response rate) of the selected HP were available during the period of the research. Results. Perceived ease of use (PEOU) of LHIMS had the strongest direct effect on perceived usefulness (PU), with a highly significant path coefficient of 0.75. PU had the greatest impact on attitude about HP’ behavioural intention to use (BIU) LHIMS to attend to patients’ healthcare delivery in CCTH (0.91). This relationship was highly significant at p < 0.001. PEOU did not have a significant direct effect on attitude about LHIMS use, as hypothesized in the original technology acceptance model. However, attitude towards use had a strong significant effect on HP’ BIU of LHIMS, with a strong statistically significant path coefficient of 0.98 at p < 0.001. Conclusions. We conclude that attitude towards use have a significant influence on HP’ behavioural intention to use LHIMS to attend to clients in Cape Coast Teaching Hospital.
Blood Eosinophils and Pulmonary Rehabilitation in COPD
Authors: Aljazeeri Jafar , Sakkat Abdullah , Makhdami Nima , Almusally Rayyan , Morfaw Frederick , McIvor Andrew
Published: November 2021

Background. Blood eosinophils predict the response to therapy, risk of exacerbation, and readmission in COPD. This study investigates whether blood eosinophils predict pulmonary rehabilitation (PR) outcomes in COPD. Methods. We categorized patients into eosinophilic (blood eosinophils ≥300 cells/ml) or noneosinophilic (<300 cells/ml). In a retrospective design, we compared changes within and between the two groups on BODE index, 6-minute walk test (6MWT), FEV1, and mMRC dyspnea scale. Results. Of 206 patients enrolled, 176 were included for analysis; 90 were eosinophilic. BODE index improved in both groups: (MD −1.25; 95% CI (−0.45, −4.25),

P
≤
0.001

) in the eosinophilic and (MD −1.33; 95% CI (−1.72, −0.94),

P
≤
0.001

) in the noneosinophilic, but a higher BODE index remained in the eosinophilic (4.98); adjusted mean change (β): 0.7 (95% CI (0.15, 1.26),

P
=
0.01

). 6MWT improved by 29.3 m in the eosinophilic (95% CI (14.2, 44.4),

P
≤
0.001

) vs. 115.1 m in the noneosinophilic (95% CI (−30.4, 260.6),

P
=
0.12

). FEV1 did not change in the eosinophilic (MD −0.6; 95% CI (−2.64, 1.48),

P
=
0.58

), but improved by 2.5% in the noneosinophilic (MD 2.5; 95% CI (0.77, 4.17),

P
=
0.005

). There were no significant between-group differences in 6MWT and FEV1; adjusted mean changes (β) were −9.69 m (95% CI (−39.51, 20.14),

P
=
0.52

) and −2.31% (95% CI (−5.69, 1.08),

P
=
0.18

), respectively. There were no significant within- or between-group changes in the mMRC scale. Conclusion. Although PR improves the BODE index in both eosinophilic and noneosinophilic COPD, a higher eosinophil count (≥300 cells/ml) is associated with a higher (worse) BODE index. Blood eosinophils may predict PR outcomes.
Morphological Measurement of the Femoral Anterior Bow in Chinese Population Based on Three‐Dimensional Computed Tomography
Authors: Liu Yang , Zhang Aobo , Cai Rui , Chen Hao , Li Chen , Han Qing , Wang Jincheng
Published: November 2021

Purpose. The femoral anterior bow is an important factor in matching a femoral implant to a femur. However, its morphology in the Chinese population has rarely been reported. In this study, a three‐dimensional measurement approach was adopted to provide accurate data. The aim was to supply a reference for designing a long‐stemmed femoral prosthesis that is more suitable for Chinese people. Methods. Computed tomography data were collected from both lower limbs of 96 normal volunteers and reconstructed into a three‐dimensional model using Mimics software. The parameters of the femoral anterior bow were measured using medical image analysis software. Statistical analysis was conducted using independent‐samples and paired‐samples t‐tests with SPSS software. Results. All the indexes showed significant sexual difference (P < 0.05). The minimum cross‐sectional area of the femoral medullary cavity was larger in men (10.77 ± 1.53 mm) than in women (9.79 ± 1.27 mm). The distance from the position of the maximum curvature to the lower edge of the lesser trochanter was also larger in men (60.93 ± 5.81 mm) than in women (56.31 ± 2.80 mm). However, the curvature of the femoral medullary cavity centerline was larger in women (883.57 ± 249.74 mm) than in men (958.79 ± 266.61 mm). The femoral anterior bow morphological indexes of Chinese subjects were different from the published data for other populations. There were no significant differences between left and right femoral anterior bows in either sex (P > 0.05). Conclusion. The three‐dimensional measurement approach adopted in this study is more convenient and accurate than previous conventional methods, with high repeatability. The morphological indexes of the femoral anterior bow in this research suggest that population characteristics should be taken into account. This study will provide references for the design of long‐stemmed femoral prostheses in the Chinese population.
Computation Offloading Optimization in Mobile Edge Computing Based on HIBSA
Authors: Liu Yang , Zhu Jin Qi , Wang Jinao
Published: November 2021

Multiaccess edge computation (MEC) is a hotspot in 5G network. The problem of task offloading is one of the core problems in MEC. In this paper, a novel computation offloading model which partitions tasks into subtasksis proposed. This model takes communication and computing resources, energy consumption of intelligent mobile devices, and weight of tasks into account. We then transform the model into a multiobjective optimization problem based on Pareto that balances the task weight and time efficiency of the offloaded tasks. In addition, an algorithm based on hybrid immune and bat scheduling algorithm (HIBSA) is further designed to tackle the proposed multiobjective optimization problem. The experimental results show that HIBSA can meet the requirements of both the task execution deadline and the weight of the offloaded tasks.
Whole-Exome Sequencing Identifies a Novel POLG Frameshift Variant in an Adult Patient Presenting with Progressive External Ophthalmoplegia and Mitochondrial DNA Depletion
Authors: Kurtz Justin , Fernandes Joseph Americo , Mansukhani Mahesh , Copeland William C. , Naini Ali B.
Published: November 2021

Mitochondrial DNA (mtDNA) depletion syndromes are a group of autosomal recessive disorders associated with a spectrum of clinical diseases, which include progressive external ophthalmoplegia (PEO). They are caused by variants in nuclear DNA (nDNA) encoded genes, and the gene that encodes for mtDNA polymerase gamma (POLG) is commonly involved. A splice-site mutation in POLG, c.3104+3A > T, was previously identified in three families with findings of PEO, and studies demonstrated this variant to result in skipping of exon 19. Here, we report a 57-year-old female who presented with ophthalmoplegia, ptosis, muscle weakness, and exercise intolerance with a subsequent muscle biopsy demonstrating mitochondrial myopathy on histopathologic evaluation and multiple mtDNA deletions by southern blot analysis. Whole-exome sequencing identified the previously characterized c. 3104+3A > T splice-site mutation in compound heterozygosity with a novel frameshift variant, p.Gly23Serfs

∗

236 (c.67_88del). mtDNA copy number analysis performed on the patient’s muscle showed mtDNA depletion, as expected in a patient with biallelic pathogenic mutations in POLG. This is the first reported case with POLG p.Gly23Serfs

∗

236, discovered in a patient presenting with features of PEO.
Pembrolizumab-Induced Adrenal Insufficiency in Patients with Untreated Advanced Non-Small Cell Lung Cancer: A Case Series
Authors: Sonehara Kei , Tateishi Kazunari , Araki Taisuke , Komatsu Masamichi , Akahane Jumpei , Yamamoto Hiroshi , Hanaoka Masayuki
Published: November 2021

Pembrolizumab-induced adrenal insufficiency (AI) is recognized as a rare immune-related adverse event (irAE) that can be fatal if diagnosis is delayed. Clinical features of AI in patients with advanced non-small cell lung cancer (NSCLC) who received pembrolizumab as the first-line treatment were observed. Five out of 49 patients with untreated advanced NSCLC developed AI between April 2017 and February 2021. Of the 5 patients, 4 developed AI with a grade >3 and were hospitalized. The median time of the onset of AI from the start of first-line treatment was 4.63 months. All the patients improved after corticosteroid replacement therapy. The efficacy of treatment was complete response in 1 patient and partial response in 4 patients. Median progression-free survival was 37.7 months, and overall survival had not been reached. This case series revealed the efficacy of immunotherapy in AI as an irAE.
Comparison of Prasugrel and Ticagrelor for Patients with Acute Coronary Syndrome: A Systematic Review and Meta-Analysis
Authors: Fong Lucas Chun Wah , Lee Nicholas Ho Cheung , Yan Andrew T. , Ng Ming-Yen
Published: November 2021

Introduction: There have been inconsistent data on the direct comparison of prasugrel and ticagrelor. This meta-analysis was conducted to summarize the current available evidence. Methods: We performed a meta-analysis (PROSPERO-registered CRD42020166810) of randomized trials up to February 2020 that compared prasugrel and ticagrelor in acute coronary syndrome with respect to the composite endpoint of myocardial infarction (MI), stroke, or cardiovascular death and secondary endpoints including MI, stroke, cardiovascular death, major bleeding (Bleeding Academic Research Consortium (BARC) type 2 or above), stent thrombosis, all-cause death, and other safety outcomes. Results: Of the 11 eligible RCTs with 6,098 patients randomized to prasugrel (n = 3,050) or ticagrelor (n = 3,048), 180 and 207 had the composite endpoint events in the prasugrel arm and the ticagrelor arm, respectively, over a weighted mean follow-up period of 11 ± 2 months. Compared with prasugrel, the ticagrelor group had similar risk in the primary composite endpoint (risk ratio [RR] = 1.17; 95% CI = 0.96–1.42; p = 0.12, I2 = 0%). Compared to prasugrel, there was no significant difference associated with the ticagrelor groups with respect to stroke (RR = 1.05; 95% CI = 0.66–1.67; p = 0.84, I2 = 0%), cardiovascular death (RR = 1.01; 95% CI = 0.75–1.36; p = 0.95, I2 = 0%), BARC type 2 or above bleeding (RR = 1.16; 95% CI = 0.89–1.52; p = 0.26, I2 = 0%), stent thrombosis (RR = 1.58; 95% CI = 0.90–2.76; p = 0.11, I2 = 0%), and all-cause death (RR = 1.10; 95% CI = 0.86–1.43; p = 0.45, I2 = 0%) except MI (RR = 1.38; 95% CI = 1.05–1.81; p = 0.02, I2 = 0%) Conclusion: Compared with prasugrel, ticagrelor did not reduce the primary composite endpoint of MI, stroke, and cardiovascular death at a weighted mean follow-up of 11 months. There was no significant difference between the secondary outcomes except MI.
Design and fabrication of rotor lateral shifting in the axial-flux permanent-magnet generator
Authors: Sari Nurma , Yudoyono Gatut , Rohedi Ali Yunus , Pramono Yono Hadi
Published: November 2021

The development of axial-flux permanent-magnet (AFPM) machines has become a mature technology. The single-stator double-rotor (SSDR) AFPM structure has advantages on the compactness and the low up to medium power applications so the microscale size and low-cost applications are reachable to be designed. The research main objectives are designing and manufacturing the lateral shifting from the north poles of the first rotor face the north poles of the second rotor (NN) to the north poles of the first rotor face the south poles of the second rotor (NS) categories as well as finding the best performance of the proposed method and implementing in a low cost and micro-scale AFPMG. The novel lateral shifting on the one of the rotors shows performance at 19.20 has the highest efficiency at 88.39% during lateral shifting from N–N (00) to N–S (360) on rotor2.
Various demand side management techniques and its role in smart grid–the state of art
Authors: Gomathinayagam Muthuselvi , Balasubramanian Saravanan
Published: November 2021

The current lifestyle of humanity relies heavily on energy consumption, thus rendering it an inevitable need. An ever-increasing demand for energy has resulted from the increasing population. Most of this demand is met by the traditional sources that continuously deplete and raise significant environmental issues. The existing power structure of developing nations is aging, unstable, and unfeasible, further prolonging the problem. The existing electricity grid is unstable, vulnerable to blackouts and disruption, has high transmission losses, low quality of power, insufficient electricity supply, and discourages distributed energy sources from being incorporated. Mitigating these problems requires a complete redesign of the system of power distribution. The modernization of the electric grid, i.e., the smart grid, is an emerging combination of different technologies designed to bring about the electrical power grid that is changing dramatically. Demand side management (DSM) allow customers to be more involved in contributors to the power systems to achieve system goals by scheduling their shiftable load. Effective DSM systems require the participation of customers in the system that can be done in a fair system. This paper focuses primarily on techniques of DSM and demand responses (DR), including scheduling approaches and strategies for optimal savings.
Biometric iris templates security based on secret image sharing and chaotic maps
Authors: Jassim Marwa Fadhel , Saeed Hamzah Wafaa mohammed , Shimal Abeer Fadhil
Published: November 2021

Biometric technique includes of uniquely identifying person based on their physical or behavioural characteristics. It is mainly used for authentication. Storing the template in the database is not a safe approach, because it can be stolen or be tampered with. Due to its importance the template needs to be protected. To treat this safety issue, the suggested system employed a method for securely storing the iris template in the database which is a merging approach for secret image sharing and hiding to enhance security and protect the privacy by decomposing the template into two independent host (public) iris images. The original template can be reconstructed only when both host images are available. Either host image does not expose the identity of the original biometric image. The security and privacy in biometrics-based authentication system is augmented by storing the data in the form of shadows at separated places instead of whole data at one. The proposed biometric recognition system includes iris segmentation algorithms, feature extraction algorithms, a (2, 2) secret sharing and hiding. The experimental results are conducted on standard colour UBIRIS v1 data set. The results indicate that the biometric template protection methods are capable of offering a solution for vulnerability that threatens the biometric template.
Early detection of slight bruises in apples by cost-efficient near-infrared imaging
Authors: Nguyen Chanh-Nghiem , Lam Van-Linh , Le Phuc-Hau , Ho Huy-Thanh , Nguyen Chi-Ngon
Published: November 2021

Near-infrared (NIR) spectroscopy has been widely reported for its useful applications in assessing internal fruit qualities. Motivated by apple consumption in the global market, this study aims to evaluate the possibility of applying NIR imaging to detect slight bruises in apple fruits. A simple optical setup was designed, and low-cost system components were used to promote the future development of practical and cost-efficient devices. To evaluate the effectiveness of the proposed approach, slight bruises were created by a mild impact with a comparably low impact energy of only 0.081 Joules. Experimental results showed that 100% of bruises in Jazz and Gala apples were accurately detected immediately after bruising and within 3 hours of storage. Thus, it is promising to develop customer devices to detect slight bruises for not only apple fruits but also other fruits with soft and thin skin at their early damage stages.
Amateur radio sensing technique using a combination of energy detection and waveform classification
Authors: Phruksahiran Narathep
Published: November 2021

A critical problem in spectrum sensing is to create a detection algorithm and test statistics. The existing approaches employ the energy level of each channel of interest. However, this feature cannot accurately characterize the actual application of public amateur radio. The transmitted signal is not continuous and may consist only of a carrier frequency without information. This paper proposes a novel energy detection and waveform feature classification (EDWC) algorithm to detect speech signals in public frequency bands based on energy detection and supervised machine learning. The energy level, descriptive statistics, and spectral measurements of radio channels are treated as feature vectors and classifiers to determine whether the signal is speech or noise. The algorithm is validated using actual frequency modulation (FM) broadcasting and public amateur signals. The proposed EDWC algorithm's performance is evaluated in terms of training duration, classification time, and receiver operating characteristic. The simulation and experimental outcomes show that the EDWC can distinguish and classify waveform characteristics for spectrum sensing purposes, particularly for the public amateur use case. The novel technical results can detect and classify public radio frequency signals as voice signals for speech communication or just noise, which is essential and can be applied in security aspects.
An improved performance routing protocol based on delay for MANETs in smart cities
Authors: Quy Vu Khanh , Chuan Pham Minh , Ngoc Le Anh
Published: November 2021

Mobile ad-hoc networks (MANETs) is a set of mobile devices that can self-configuration, self-established parameters to transmission in-network. Although limited inability, MANETs have been applied in many domains to serve humanity in recent years, such as disaster recovery, forest fire, military, intelligent traffic, or IoT ecosystems. Because of the movement of network devices, the system performance is low. In order to MANETs could more contribution in the future of the Internet, the routing is a significant problem to enhance the performance of MANETs. In this work, we proposed a new delay-based protocol aim enhance the system performance, called performance routing protocol based on delay (PRPD). In order to analyze the efficiency of the proposed solution, we compared the proposed protocol with traditional protocols. Experiment results showed that the PRPD protocol improved packet delivery ratio, throughput, and delay compared to the traditional protocols.
A design of a multi-agent recommendation system using ontologies and rule-based reasoning: pandemic context
Authors: Ouatiq Amina , ElGuemmat Kamal , Mansouri Khalifa , Qbadou Mohammed
Published: November 2021

Learners attend their courses in remote or hybrid systems find it difficult to follow one size fits all courses. These difficulties have increased with the pandemic, lockdown, and the stress they cause. Hence, the role of adaptive systems to recommend personalized learning resources according to the learner's profile. The purpose of this paper is to design a system for recommending learning objects according learner's condition, including his mental state, his COVID-19 history, as well as his social situation and ability to connect to the e-learning system on a regular basis. In this article, we present an architecture of a recommendation system for personalized learning objects based on ontologies and on rule-based reasoning, and we will also describe the inference rules required for the adaptation of the educational content to the needs of the learners, taking into account the learner’s health and mental state, as well as his social situation. The system designed, and validated using the unified modeling language (UML). It additionally allows teachers to have a holistic view of learners’ progress and situations.
Modelling on-demand preprocessing framework towards practical approach in clinical analysis of diabetic retinopathy
Authors: Mandya Krishnegowda Prakruthi , Ganesan Komarasamy
Published: November 2021

Diabetic retinopathy (DR) refers to a complication of diabetes and a prime cause of vision loss in middle-aged people. A timely screening and diagnosis process can reduce the risk of blindness. Fundus imaging is mainly preferred in the clinical analysis of DR. However; the raw fundus images are usually subjected to artifacts, noise, low and varied contrast, which is very hard to process by human visual systems and automated systems. In the existing literature, many solutions are given to enhance the fundus image. However, such approaches are particular and limited to a specific objective that cannot address multiple fundus images. This paper has presented an on-demand preprocessing frame work that integrates different techniques to address geometrical issues, random noises, and comprehensive contrast enhancement solutions. The performance of each preprocessing process is evaluated against peak signal-to-noise ratio (PSNR), and brightness is quantified in the enhanced image. The motive of this paper is to offer a flexible approach of preprocessing mechanism that can meet image enhancement needs based on different preprocessing requirements to improve the quality of fundus imaging towards early-stage diabetic retinopathy identification.
A novel weather parameters prediction scheme and their effects on crops
Authors: Lingaraju Naveen , Savalegowda Mohan Hosaagrahara
Published: November 2021

Weather forecast is significantly imperative in today’s smart technological world. A precise forecast model entails a plentiful data in order to attain the most accurate predictions. However, a forecast of future rainfall from historical data samples has always been challenging and key area of research. Hence, in modern weather forecasting a combo of computer models, observation, and knowledge of trends and patterns are introduced. This research work has presented a fitness function based adaptive artificial neural network scheme in order to forecast rainfall and temperature for upcoming decade (2021-2030) using historical weather data of 20 different districts of Karnataka state. Furthermore, effects of these forecasted weather parameters are realized over five major crops of Karnataka namely rice, wheat, jowar, maize, and ragi with the intention of evaluation for efficient crop management in terms of the passing relevant messages to the farmers and alternate measures such as suggesting other geographical locations to grow the same crop or growing other suitable crops at same geographical location. A graphical user interface (GUI) application has been developed for the proposed work in order to ease out the flow of work.
Building Quranic stories ontology using MappingMaster domain-specific language
Authors: Alsalhee Rusul Yousif , Abdullah Abdulhussein Mohsin
Published: November 2021

The Holy Quran, due to it is full of many inspiring stories and multiple lessons that need to understand it requires additional attention when it comes to searching issues and information retrieval. Many works were carried out in the Holy Quran field, but some of these dealt with a part of the Quran or covered it in general, and some of them did not support semantic research techniques and the possibility of understanding the Quranic knowledge by the people and computers. As for others, techniques of data analysis, processing, and ontology were adopted, which led to directed these to linguistic aspects more than semantic. Another weakness in the previous works, they have adopted the method manually entering ontology, which is costly and time-consuming. In this paper, we constructed the ontology of Quranic stories. This ontology depended in its construction on the MappingMaster domain-specific language (MappingMaster DSL)technology, through which concepts and individuals can be created and linked automatically to the ontology from Excel sheets. The conceptual structure was built using the object role modeling (ORM) modeling language. SPARQL query language used to test and evaluate the propsed ontology by asking many competency questions and as a result, the ontology answered all these questions well.
Optimizing of the installed capacity of hybrid renewable energy with a modified MPPT model
Authors: Utomo Sukarno Budi , Setiawan Iwan , Fajar Berkah , Winoto Sonny Hady , Marwanto Arief
Published: November 2021

The lack of wind speed capacity and the emission of photons from sunlight are the problem in a hybrid system of photovoltaic (PV) panels and wind turbines. To overcome this shortcoming, the incremental conductance (IC) algorithm is applied that could control the converter work cycle and the switching of the buck boost therefore maximum efficiency of maximum power point tracking (MPPT) is reached. The operation of the PV-wind hybrid system, consisting of a 100 W PV array device and a 400 W wind subsystem, 12 V/100 Ah battery energy storage and LED, the PV-wind system requires a hybrid controller for battery charging and usage and load lamp and it’s conducted in experimental setup. The experimental has shown that an average increase in power generated was 38.8% compared to a single system of PV panels or a single wind turbine sub-system. Therefore, the potential opportunities for increasing power production in the tropics wheather could be carried out and applied with this model.
Solving multiple linear regression problem using artificial neural network
Authors: Khrisat Mohammad S. , Alqadi Ziad A.
Published: November 2021

Multiple linear regressions are an important tool used to find the relationship between a set of variables used in various scientific experiments. In this article we are going to introduce a simple method of solving a multiple rectilinear regressions (MLR) problem that uses an artificial neural network to find the accurate and expected output from MLR problem. Different artificial neural network (ANN) types with different architecture will be tested, the error between the target outputs and the calculated ANN outputs will be investigated. A recommendation of using a certain type of ANN based on the experimental results will be raised.
IoT-based sound-level control for audio amplifiers: mosques as a case study
Authors: Al-Oudat Naeem
Published: November 2021

When using audio-amplifiers in the open, uneven distribution of sound makes people unpleasant because it is loud or unheared. This unfortunate situation arises because audio-amplifiers volumes are set according to the guess of sound technicians. Mosques, as an example, are distributed inside wide areas and fire Azan five times a day. Due to the relatively long distances between them, speed and direction of the wind impose setting sound levels prior to each Azan such that all the area is covered and the overlap is minimized. In this paper, we propose a system based on internet of things (IoT) model to control the sound level of each mosque in the community. An IoT device (one in a mosque) sets the level of sound fired by the audio-amplifier. To do that, a synchronized series of tones is fired from each node. Once a node hears these tones, the process of sound level control starts to indicate the distances to heared nodes. As the approximate distances between nodes are known, each node can calculate its suitable sound level. Results showed that the proposed system is effective in setting sound levels for mosques audio amplifiers.
Validation of photovoltaics powered UPQC using ANFIS controller in a standard microgrid test environment
Authors: S Sumana , R Dhanalakshmi , S Dhamodharan
Published: November 2021

The power quality improvement becomes one of the important tasks while using microgrid as main power supply. Because the microgrid is combination of renewable energy resources. The renewable energy resources are intermittent in power supply and at the peak loading condition it has to supply the required power. So, the power quality problems may increase in that time. Out of all power quality issues the voltage drop and harmonic distortion is considered as the most serious one. In recent years unified power quality conditioner (UPQC) is emerged as most promising device which compensates both utility as well as customer side power quality disturbances in effective way. The compensating potentiality used in the UPQC is limited by the use of DC link voltage regulation and the conventional proportional integral (PI) controller. In this paper the compensating potentiality of the UPQC device is controlled by an adaptive neuro fuzzy inference system (ANFIS) control and it is powered from the available photovoltaics (PV) power generation. The effect of adding an intelligent UPQC is tested in the standard IEEE-14bus environment. MATLAB 2017b is used here for testing and plotting the simulation results.
New algorithm for clustering unlabeled big data
Authors: Mohammed Marwan B. , AL-Hameed Wafaa
Published: November 2021

The clustering analysis techniques play an important role in the area of data mining. Although from existence several clustering techniques. However, it still to their tries to improve the clustering process efficiently or propose new techniques seeks to allocate objects into clusters so that two objects in the same cluster are more similar than two objects in different clusters and careful not to duplicate the same objects in different groups with the ability to cover all data as much as possible. This paper presents two directions. The first is to propose a new algorithm that coined a name (MB Algorithm) to collect unlabeled data and put them into appropriate groups. The second is the creation of a lexical sequence sentence (LCS) based on similar semantic sentences which are different from the traditional lexical word chain (LCW) based on words. The results showed that the performance of the MB algorithm has generally outperformed the two algorithms the hierarchical clustering algorithm and the K-mean algorithm.