bluuebunny/crossref_metadata_2025 huggingface dataset:
Analisis Biomekanika Pada Postur dan Gerak Tubuh Operator Book Lift Guna Mengidentifikasi Risk of Musculoskeletal Disorders
Authors:   Universitas Teknologi Yogyakarta, Alfandianto Alex , Putri Margaretha Hernita Erni Dwi ,   Universitas Katolik Musi Charitas
Published: November 2022

Manual Material Handling (MMH) is expressed as an art and science that includes handling, transfer, packing, storage and monitoring. In this study, the problems faced by the book lift operator are less attention to the risk of spinal cord injury, the operator should pay attention to the safety and health level, to know the biomechanical hazard factors, as well as the MMH activity that endanger or cause pain in the operator. The observations focused on one binder carrier operator at the APK Laboratory, which is the part that moves the book directly from the floor to the point of stomach inclination or the designated destination location with a book weight of 8 kg. The identification of this case studyuses a biomechanical approach to find out the compressive forces at an inclination angle. The yield of compressive force of the inclination angle is -22572.3 Nand -29972,9 Nagainst the L5 / S1 compression reference standard, the comparative value must be below 3400 N, in order to obtain safe operator category. So the results of these comparisons have a relation or synopsis of posture and body movements of operators belonging to the category safe or not occur Risk of Musculoskeletal Disorders.
Perancangan Tata Letak Hasil Produksi Buis Berdasarkan ARC
Authors: . Ernita , Syahmer Verra , Rachman Boby
Published: November 2022

The layout of the facilities which is good and in accordance with the state of the company is one factor for the orderly and efficient arrangement of all facilities. The current problems that encountered in Yalesvava CV is the result of the production being constrained in the placement of the layout where the results of the resulting production due to sequence of irregular processes thereby resulting in accumulation of products that result in irregularity. Therefore, it is necessary to arrange the layout of production facilities in order to design buis layout based on ARC understanding and layout design layout design model from ARC understanding. Based on the background, the research objectives are: to produce layout design based on ARC understanding and layout design from ARC understanding. The result of this research is the finding that there are some work areas that must be moved or not moved and the discovery of the work area which is not appropriate in case it is make difficult to access. The advice given to CV. Yalesvava is maintaining the layout of raw material area so that it is not disturb the existing work access, to place the production result according to the product made by grouping the buis size, the printing can be done directly according to the specified size.
Desain RPS Mata Kuliah Perancangan Sistem Kerja& Ergonomi Berbasis Nilai-Nilai Dasar CHAMPION
Authors:   Universitas Katolik Musi Charitas, Setiawan Heri
Published: November 2022

This study aims to obtain concrete examplesdesign of Semester Learning Plans (RPS) Work System Design & Ergonomics (PSKE) courses based on CHAMPION core values include; Charity, Humanity, Altruism, Managing-capacity, Persistence, Integrity, Open-minded, and Noveltyfrom Industrial Engineering Study Program, Musi Charitas Catholic University with the KKNI program. The basis of harmonization and internalization of the core values of CHAMPION in RPS will give a distinctive characteristic to other universities. Harmonization of RPS is very possible to produce a working system design of the teaching and learning process that is reviewed systemically, holistically, interdisciplinary and participatory so that it has an impact on effective, comfortable, safety, healthy and efficient (ENASE) so that productivity can be optimized. Based on the results of the RPS design study PSKE course, learning outcomes include; the impact attitudes and values of 29.58%, general skills of 14.79%, special skills of 33.80%, and mastery of knowledge of 21.83%. Three interesting learning methods are obtained, namely; student-centered learning is 39.47%, interaction/group discussion is 32.89%, and project-based is 27.63%. Interesting learning experiences, namely; assignments by 29%, compilation of papers by 27%, practice by 20%, surveys or visits by 16%, and comparative studies of 8%. Selected assessment criteria/rubrics, namely; assignment test as learning, project, portfolio of 35.9%, written test of 30.9%, performance test of 16.9%, observation test of 7%, and participation test of 2.8%.
Change in the Importance of Ethnicity and Religiosity in the British Armed Forces from the Perspective of the Military Chaplaincy
Authors: Paroda Zsolt
Published: November 2022

Like the armed forces of every country, the British Army is undergoing constant structural change and is doing so to respond to the latest challenges of its time. As part of this process, a clear trend in the personnel composition is becoming apparent, playing a catalyst for change. My working hypothesis is that ethnic and religious change should be the primary focus, precisely because these two factors, and changes in the proportion of these factors, are currently seen as having the most significant impact on military chaplaincy. Furthermore, by looking at these transformations, the growing number of theoretical challenges to the organisation of chaplaincy and the increasing number of practical obstacles to chaplains themselves can be best understood. I will use qualitative method to prove my hypothesis, utilising statistical data and personal narratives. Methods and rules to address the problems that arise without any criteria are not currently in place in the British Army, as it seems that at the moment, even amid change, only flexible responses to these challenges can be given, as the situation demands. I will focus on these at the end of the thesis alongside forecasting the upcoming resolutions.
PEMBERIAN BAHAN ORGANIK DAN PENINGKATAN KESUBURAN TANAH PADA LAHAN KOPI LIBERICA TANGSE KABUPATEN PIDIE
Authors: Helmi Helmi , Ilyas Ilyas , Khalil Munawar , Putra Iwandikasyah , Afrizal Afrizal
Published: November 2022

Tujuan dari penelitian ini adalah untuk meningkatkan produktivitas lahan yang berkelanjutan dengan menerapkan bahan organik. Penggunaan bahan organik kascing, pupuk kulit buah, dan kotoran sapi dalam jangka panjang diharapkan mampu memperbaiki sifat fisik tanah pada tanaman kopi Liberica (Coffea liberica var). Penelitian dilakukan di perkebunan kopi Liberica Kecamatan Tangse Kabupaten Pidie. Penelitian ini menggunakan rancangan acak faktorial pola bersarang dengan 2 faktor: (1) perlakuan bahan organik (kontrol, vermikompos, pupuk kulit buah kopi, dan kotoran sapi), (2) tingkat kedalaman tanah (0-10 cm, 10-20 cm, dan 20-30 cm tinggi dibandingkan dengan aplikasi pupuk kulit kopi, kotoran sapi pada kedalaman 0-10 cm. Aplikasi berbagai bahan organik tidak meningkatkan bahan organik tanaman. tanah pada kedalaman 10-20 dan 20-30 cm Aplikasi vermikompos, pupuk kulit kopi dan kotoran sapi meningkatkan stabilitas agregat dibandingkan tanpa aplikasi bahan organik (NPK) Bahan organik memiliki hubungan positif dengan stabilitas agregat tanah di kedalaman 0-10 cm (r = 61%), sehingga semakin tinggi kandungan bahan organik maka stabilitas agregat tanah semakin tinggi, sedangkan pada kedalaman 10-20 cm dan 20-30 cm tidak ada hubungan yang signifikan.
Analisis Implementasi Green Banking Sustainability dan Kinerja Keuangan Terhadap Profitabilitas Perbankan yang Terdaftar di Bursa Efek Indonesia Tahun 2012-2018
Authors: Siahaan Christy , Silalahi Amlys Syahputra , Syahyunan Syahyunan , Sianipar Aryanti Sariartha
Published: November 2022

Penelitian ini bertujuan untuk mengetahui dampak dari green banking dan kinerja keuangan terhadap profitabilitas bank. Green banking dalam penelitian ini dibagi menjadi dua dimensi yakni, transaksi non tunai (e-banking) dan kebijakan green banking. Kinerja keuangan dalam penelitian ini adalah ukuran bank, kecukupan modal, kredit bermasalah, efisiensi bank dan tingkat likuiditas bank. Populasi pada penelitian ini adalah 43 perusahaan sektor perbankan yang terdaftar di Bursa Efek Indonesia periode 2012-2018. Sampel pada penelitian ini adalah 9 bank terpilih dengan menggunakan metode purposive sampling. Metode analisis pada penelitian ini adalah analisis regresi data panel. Hasil menunjukkan bahwa Transaksi Non Tunai, Kecukupan Modal, Kredit Bermasalah dan Tingkat Likuiditas bank masingmasing berpengaruh negatif dan tidak signifikan terhadap profitabilitas bank. Kebijakan Green banking berpengaruh secara positif dan tidak signifikan. Ukuran Bank dan Efisiensi Bank masing-masing berpengaruh secara negatif dan signifikan terhadap profitabilitas bank.

This study aims to determine the impact of green banking and financial performance on bank profitability. Green banking in this study is divided into two dimensions namely, non-cash transactions (e-banking) and green banking policy. Financial performance in this study is bank size, capital adequacy ratio, non-performing loans, bank efficiency and bank’s liquidity. The population of the research are 43 companies from the banking sector that listed in Indonesia Stock Exchange with the period 2012-2018. The sample of this research is 9 banks that chose using purposive sampling method that listed in Indonesia Stock Exchange with period 2012-2018. The method of analysis in this study is panel data regression analysis. The results show that Non-Cash Transactions, Capital Adequacy, Non-performing Loans and Bank’s Liquidity have a negative and not significant effect on bank profitability. Meanwhile, Green Banking Policy has a positive and insignificant effect, and Bank Size and Bank Efficiency have a negative and significant effect on profitability bank.
Effect of Promotional Mix And Price On Consumer Subscription Decisions Mediated By Trust In Indihome Consumers In Medan" (Emperis Study On PT. Telkom Witel Medan)
Authors: Adika Fajar Putra  , Lubis Muhammad Arif
Published: November 2022

Indihome is a result of PT. Telkom. This examination means to analyze the impact of Promotion Mix (X1) and Price (X2) on Decision (Y) interceded by Trust (Z) Indihome Customers at PT Telkom Witel around there. Tests were taken upwards of 85 Indihome clients in Medan City utilizing an underlying condition model (Structural Equation Model). Information assortment utilized a poll while information investigation utilized Structural Equation Modeling (SEM) with Smart Partial Least Square (Smart PLS) adaptation 3.0 M3 programming. Test outcomes: 1. Advancement Mix significantly affects Consumer Decisions to buy in to Indihome in, 2. Costs significantly affect Consumer Decisions to buy in to Indihome, 3. Advancement Mix significantly affects Indihome Customer Confidence, 4. Costs significantly affect Indihome Consumer Confidence, 5. Trust significantly affects Consumer Decision to buy in to Indihome.
Employee Performance Assessment With Human Resources Scorecard And AHP Method (Case Study : PT PLN (PERSERO) North Sumatra Generation)
Authors: Lubis Andrew Satria , Alfi Amalia
Published: November 2022

How does PT. PLN KITSBU measures the performance of human resources. PT. PLN KITSBU utilizes the Employee Performance Information System (SIMKP) application. By using the human resource scorecard and AHP (Analytic Hierarchy Process) method, you can get employee performance evaluations that have never been done in a company. The human resources scorecard method itself is a measurement system that connects human resources with strategy. Then, the AHP method is used to make employee performance decisions. The purpose of this study is to determine employee performance indicators and to find weights from all angles. And suggestions for companies, with which to improve in the future. The research results obtained 18 KPIs from 4 perspectives (including 4 KPIs from financial perspective, 3 KPIs for consumers or consumers, 7 KPIs for internal business composition and 4 KPIs for growth and learning). From a financial perspective, the weighted score is 3.341 (moderate), customers or consumers are 3.524 (good), the composition of the internal business is 3.357 (moderate), and growth and learning is 3.38 (moderate).
Al-Washliyah Business Management Strategy Analysis of North Sumatra Al-Washliyah
Authors: Burhanuddin  , Ratna Sari Dewitra  , Ayu Ulandari
Published: November 2022

Al Jam'iyatul Washliyah is an Islamic community organization that was born on November 30, 1930 in Medan, North Sumatra. This study aims to explore the management strategy of Al Jam'iyatul Washliyah's charitable business. This research is classified as field research. That way the object of research is an object in the field that is able to provide information about research studies. This research shows that, on the one hand, Al-Washliyah's charitable efforts already exist in carrying out their functions in the organization. On the other hand, the Al-Washliyah organization has not been able to fully overcome the problems of managing its business charity. The main finding produced in this study, is that the organization has not been able to enforce regulations according to the demands of AD/ART AW, as a result, Al-Washliyah's charitable efforts have not been able to fully regulate organization, assets and administrative order.
Only the good cry: Investigating the relationship between crying proneness and moral judgments and behavior
Authors: Zickfeld Janis H. , Kamble Shanmukh , Oostelbos Romy , Vingerhoets Ad
Published: November 2022

People cry for various reasons and in numerous situations, some involving highly moral aspects such as altruism or moral beauty. At the same time, criers have been found to be evaluated as more morally upright—they are perceived as more honest, reliable, and sincere than non-criers. The current project provides a first comprehensive investigation to test whether this perception is adequate. Across six studies sampling Dutch, Indian, and British adults (N = 2325), we explored the relationship between self-reported crying proneness and moral judgments and behavior, employing self-report measures and actual behavior assessments. Across all studies, we observed positive correlations of crying proneness with moral judgments (r = .27 [.17, .38]) and prosocial behavioral tendencies and behaviors (r = .20 [.12, .28]). These associations held in three (moral judgment) or two (prosocial tendencies and behaviors) out of five studies when controlling for other important variables. Thus, the current project provides first evidence that crying is related to moral evaluation and behavior, and we discuss its importance for the literature on human emotional crying.
Multidimensional fetal flow imaging with cardiovascular magnetic resonance: a feasibility study
Authors: Goolaub Datta Singh , Roy Christopher W. , Schrauben Eric , Sussman Dafna , Marini Davide , Seed Mike , K Macgowan Christopher
Published: November 2022

Purpose: To image multidimensional flow in fetuses using golden-angle radial phase contrast cardiovascular magnetic resonance (PC-CMR) with motion correction and retrospective gating.

Methods: A novel PC-CMR method was developed using an ungated golden-angle radial acquisition with continuously incremented velocity encoding. Healthy subjects (n=5, 27 +/- 3 years, males) and pregnant females (n=5, 34 +/- 2 weeks gestation) were imaged at 3T using the proposed sequence. Real-time reconstructions were first performed for retrospective motion correction and cardiac gating (using metric optimized gating, MOG). CINE reconstructions of multidimensional flow were then performed using the corrected and gated data.

Results: In adults, flows obtained using the proposed method agreed strongly with those obtained using a conventionally gated Cartesian acquisition. Across the five adults, bias and limits of agreement were -1.0 cm/s and [-5.1, 3.2] cm/s for mean velocities and -1.1 cm/s and [-6.5, 4.3] cm/s for peak velocities. Temporal correlation between corresponding waveforms was also high (R similar to 0.98). Calculated timing errors between MOG and pulse-gating RR intervals were low (similar to 20 ms). First insights into multidimensional fetal blood flows were achieved. Inter-subject consistency in fetal descending aortic flows (n=3) was strong with an average velocity of 27.1 +/- 0.4 cm/s, peak systolic velocity of 70.0 +/- 1.8 cm/s and an intra-class correlation coefficient of 0.95 between the velocity waveforms. In one fetal case, high flow waveform reproducibility was demonstrated in the ascending aorta (R = 0.97) and main pulmonary artery (R = 0.99).

Conclusion: Multidimensional PC-CMR of fetal flow was developed and validated, incorporating retrospective motion compensation and cardiac gating. Using this method, the first quantification and visualization of multidimensional fetal blood flow was achieved using CMR.
Medical Augmentation (Med-Aug) for Optimal Data Augmentation in Medical Deep Learning Networks
Authors: Lo Justin , Cardinell Jillian , Costanzo Alejo , Sussman Dafna
Published: November 2022

Deep learning (DL) algorithms have become an increasingly popular choice for image classification and segmentation tasks; however, their range of applications can be limited. Their limitation stems from them requiring ample data to achieve high performance and adequate generalizability. In the case of clinical imaging data, images are not always available in large quantities. This issue can be alleviated by using data augmentation (DA) techniques. The choice of DA is important because poor selection can possibly hinder the performance of a DL algorithm. We propose a DA policy search algorithm that offers an extended set of transformations that accommodate the variations in biomedical imaging datasets. The algorithm makes use of the efficient and high-dimensional optimizer Bi-Population Covariance Matrix Adaptation Evolution Strategy (BIPOP-CMA-ES) and returns an optimal DA policy based on any input imaging dataset and a DL algorithm. Our proposed algorithm, Medical Augmentation (Med-Aug), can be implemented by other researchers in related medical DL applications to improve their model's performance. Furthermore, we present our found optimal DA policies for a variety of medical datasets and popular segmentation networks for other researchers to use in related tasks.

 
An image-based flow cytometric approach to the assessment of the nucleus-to-cytoplasm ratio
Authors: Sebastian Joseph A. , Moore Michael
J. , Berndl Elizabeth S. L. , Kolios Michael
Published: November 2022

The nucleus-to-cytoplasm ratio (N:C) can be used as one metric in histology for grading certain types of tumor malignancy. Current N:C assessment techniques are time-consuming and low throughput. Thus, in high-throughput clinical contexts, there is a need for a technique that can assess cell malignancy rapidly. In this study, we assess the N:C ratio of four different malignant cell lines (OCI-AML-5—blood cancer, CAKI-2—kidney cancer, HT-29— colon cancer, SK-BR-3—breast cancer) and a non-malignant cell line (MCF-10A –breast epithelium) using an imaging flow cytometer (IFC). Cells were stained with the DRAQ-5 nuclear dye to stain the cell nucleus. An Amnis ImageStreamX®IFC acquired brightfield/ fluorescence images of cells and their nuclei, respectively. Masking and gating techniques were used to obtain the cell and nucleus diameters for 5284 OCI-AML-5 cells, 1096 CAKI-2 cells, 6302 HT-29 cells, 3159 SK-BR-3 cells, and 1109 MCF-10A cells. The N:C ratio was calculated as the ratio of the nucleus diameter to the total cell diameter. The average cell and nucleus diameters from IFC were 12.3±1.2μm and 9.0±1.1μm for OCI-AML5 cells, 24.5±2.6μm and 15.6±2.1μm for CAKI-2 cells, 16.2±1.8μm and 11.2±1.3μm for HT29 cells, 18.0±3.7μm and 12.5±2.1μm for SK-BR-3 cells, and 19.4±2.2μm and 10.1± 1.8μm for MCF-10A cells. Here we show a general N:C ratio of ~0.6–0.7 across varying malignant cell lines and a N:C ratio of ~0.5 for a non-malignant cell line. This study demonstrates the use of IFC to assess the N:C ratio of cancerous and non-cancerous cells, and the promise of its use in clinically relevant high-throughput detection scenarios to supplement current workflows used for cancer cell grading.
Feasibility of detecting change in backscattered energy of acoustic harmonics in locally heated tissues
Authors: Maraghechi Borna , Kolios Michael , Tavakkoli Jahangir (Jahan)
Published: November 2022

Purpose: A real-time noninvasive thermometry technique is required to estimate the temperature distribution during hyperthermia to monitor and control the treatment. The main objective of this study is to demonstrate the possibility of detecting change in backscatter energy (CBE) of acoustic harmonics in tissue-mimicking gel phantoms and ex vivo bovine muscle tissues in which the temperature was locally increased within the hyperthermia regime. Materials and Methods: A peristaltic pump was used to circulate hot water through a needle inserted inside the samples to locally increase the temperature from 26?C to 46 ?C. The CBE of acoustic harmonics were used to identify the location of temperature changes in the samples. A conventional echo-shift technique was also implemented for comparison. Data collection was performed for two conditions to investigate the effect of motion on both techniques by: (1) inducing vibration in the sample through the peristatic pump and, (2) subsequently with no sample vibration while the pump was off. Results: Harmonics were able to determine the location of temperature rise in the presence and absence of vibration. In gel phantom, the mean contrast to noise ratio (CNR) in CBE maps reduced by a factor of 0.86 due to vibration whereas in gradient maps the CNR reduced by a factor of 8.3. Conclusions: The findings of this study suggest that the change in backscatter energy of acoustic harmonics can potentially be used to develop a noninvasive ultrasound-based thermometry technique with lower susceptibility to motion artifacts compared to the echo-shift method.
Comparison of methods for texture analysis of QUS parametric images in the characterization of breast lesions
Authors: Osapoetra Laurentius O. , Chan William , Kolios Michael , Czarnota Gregory  J.
Published: November 2022

Purpose

Accurate and timely diagnosis of breast carcinoma is very crucial because of its high incidence and high morbidity. Screening can improve overall prognosis by detecting the disease early. Biopsy remains as the gold standard for pathological confirmation of malignancy and tumour grading. The development of diagnostic imaging techniques as an alternative for the rapid and accurate characterization of breast masses is necessitated. Quantitative ultrasound (QUS) spectroscopy is a modality well suited for this purpose. This study was carried out to evaluate different texture analysis methods applied on QUS spectral parametric images for the characterization of breast lesions.

Methods

Parametric images of mid-band-fit (MBF), spectral-slope (SS), spectral-intercept (SI), average scatterer diameter (ASD), and average acoustic concentration (AAC) were determined using QUS spectroscopy from 193 patients with breast lesions. Texture methods were used to quantify heterogeneities of the parametric images. Three statistical-based approaches for texture analysis that include Gray Level Co-occurrence Matrix (GLCM), Gray Level Run-length Matrix (GRLM), and Gray Level Size Zone Matrix (GLSZM) methods were evaluated. QUS and texture-parameters were determined from both tumour core and a 5-mm tumour margin and were used in comparison to histopathological analysis in order to classify breast lesions as either benign or malignant. We developed a diagnostic model using different classification algorithms including linear discriminant analysis (LDA), k-nearest neighbours (KNN), support vector machine with radial basis function kernel (SVM-RBF), and an artificial neural network (ANN). Model performance was evaluated using leave-one-out cross-validation (LOOCV) and hold-out validation.

Results

Classifier performances ranged from 73% to 91% in terms of accuracy dependent on tumour margin inclusion and classifier methodology. Utilizing information from tumour core alone, the ANN achieved the best classification performance of 93% sensitivity, 88% specificity, 91% accuracy, 0.95 AUC using QUS parameters and their GLSZM texture features.

Conclusions

A QUS-based framework and texture analysis methods enabled classification of breast lesions with >90% accuracy. The results suggest that optimizing method for extracting discriminative textural features from QUS spectral parametric images can improve classification performance. Evaluation of the proposed technique on a larger cohort of patients with proper validation technique demonstrated the robustness and generalization of the approach.
Feasibility of optical coherence elastography measurements of shear wave propagation in homogeneous tissue equivalent phantoms
Authors: Razani Marjan , Mariampillai Adrian , Sun Cuiru , Wan Hei Luk Timothy , Yang Victor X. D. , Kolios Michael
Published: November 2022

In this work, we explored the potential of measuring shear wave propagation using optical coherence elastography (OCE) based on a sweptsource optical coherence tomography (OCT) system. Shear waves were generated using a 20 MHz piezoelectric transducer (circular element 8.5 mm diameter) transmitting sine-wave bursts of 400 μs, synchronized with the OCT swept source wavelength sweep. The acoustic radiation force (ARF) was applied to two gelatin phantoms (differing in gelatin concentration by weight, 8% vs. 14%). Differential OCT phase maps, measured with and without the ARF, demonstrate microscopic displacement generated by shear wave propagation in these phantoms of different stiffness. We present preliminary results of OCT derived shear wave propagation velocity and modulus, and compare these results to rheometer measurements. The results demonstrate the feasibility of shear wave OCE (SW-OCE) for high-resolution microscopic homogeneous tissue mechanical property characterization. 
Ramanujan Sums for Image Pattern Analysis
Authors: Chen Guangyi , Krishnan Sridhar , Bui Tien D.
Published: November 2022

Ramanujan sums (RS) have been found to be very successful in signal processing recently. However, as far as we know, the RS have not been applied to image analysis. In this paper, we propose two novel algorithms for image analysis, including moment invariants and pattern recognition. Our algorithms are invariant to the translation, rotation and scaling of the 2D shapes. The RS are robust to Gaussian white noise and occlusion as well. Our algorithms compare favourably to the dual-tree complex wavelet (DTCWT) moments and the Zernike’s moments in terms of correct classification rates for three well-known shape datasets. 
Interference Excision in Spread Spectrum Communications Using Adaptive Positive Time-Frequency Analysis
Authors: Krishnan Sridhar , Erküçük Serhat
Published: November 2022

This paper introduces a novel algorithm to excise single and multicomponent chirp-like interferences in direct sequence spread spectrum (DSSS) communications. The excision algorithm consists of two stages: adaptive signal decomposition stage and directional element detection stage based on the Hough-Radon transform (HRT). Initially, the received spread spectrum signal is decomposed into its time-frequency (TF) functions using an adaptive signal decomposition algorithm, and the resulting TF functions are mapped onto the TF plane. We then use a line detection algorithm based on the HRT that operates on the image of the TF plane and detects energy varying directional elements that satisfy a parametric constraint. Interference is modeled by reconstructing the corresponding TF functions detected by the HRT, and subtracted from the received signal. The proposed technique has two main advantages: (i) it localizes the interferences on the TF plane with no cross-terms, thus facilitating simple filtering techniques based on thresholding of the TF functions, and is an efficient way to excise the interference; (ii) it can be used for the detection of any directional interferences that can be parameterized. Simulation results with synthetic models have shown successful performance with linear and quadratic chirp interferences for single and multicomponent interference cases. The proposed method excises the interference even under very low SNR conditions of −10 dB, and the technique could be easily extended to any interferences that could be represented by a parametric equation in the TF plane. 
Parametric Time-Frequency Analysis and Its Applications in Music Classification
Authors: Shen Ying , Li Xiaoli , Ma Ngok-Wah , Krishnan Sridhar
Published: November 2022

Analysis of nonstationary signals, such as music signals, is a challenging task. The purpose of this study is to explore an efficient and powerful technique to analyze and classify music signals in higher frequency range (44.1 kHz). The pursuit methods are good tools for this purpose, but they aimed at representing the signals rather than classifying them as in Y. Paragakin et al., 2009. Among the pursuit methods, matching pursuit (MP), an adaptive true nonstationary time-frequency signal analysis tool, is applied for music classification. First, MP decomposes the sample signals into time-frequency functions or atoms. Atom parameters are then analyzed and manipulated, and discriminant features are extracted from atom parameters. Besides the parameters obtained using MP, an additional feature, central energy, is also derived. Linear discriminant analysis and the leave-one-out method are used to evaluate the classification accuracy rate for different feature sets. The study is one of the very few works that analyze atoms statistically and extract discriminant features directly from the parameters. From our experiments, it is evident that the MP algorithm with the Gabor dictionary decomposes nonstationary signals, such as music signals, into atoms in which the parameters contain strong discriminant information sufficient for accurate and efficient signal classifications. 
On the Use of Complementary Spectral Features for Speaker Recognition
Authors: Hosseinzadeh Danoush , Krishnan Sridhar
Published: November 2022

 The most popular features for speaker recognition are Mel frequency cepstral coefficients (MFCCs) and linear prediction cepstral coefficients (LPCCs). These features are used extensively because they characterize the vocal tract configuration which is known to be highly speaker-dependent. In this work, several features are introduced that can characterize the vocal system in order to complement the traditional features and produce better speaker recognition models. The spectral centroid (SC), spectral bandwidth (SBW), spectral band energy (SBE), spectral crest factor (SCF), spectral flatness measure (SFM), Shannon entropy (SE), and Renyi entropy (RE) were utilized for this purpose. This work demonstrates that these features are robust in noisy conditions by simulating some common distortions that are found in the speakers’ environment and a typical telephone channel. Babble noise, additive white Gaussian noise (AWGN), and a bandpass channel with 1 dB of ripple were used to simulate these noisy conditions. The results show significant improvements in classification performance for all noise conditions when these features were used to complement the MFCC and ΔMFCC features. In particular, the SC and SCF improved performance in almost all noise conditions within the examined SNR range (10–40 dB). For example, in cases where there was only one source of distortion, classification improvements of up to 8% and 10% were achieved under babble noise and AWGN, respectively, using the SCF feature. 
A Joint Time-Frequency and Matrix Decomposition Feature Extraction Methodology for Pathological Voice Classification
Authors: Ghoraani Behnaz , Krishnan Sridhar
Published: November 2022

 The number of people affected by speech problems is increasing as the modern world places increasing demands on the human voice via mobile telephones, voice recognition software, and interpersonal verbal communications. In this paper, we propose a novel methodology for automatic pattern classification of pathological voices. The main contribution of this paper is extraction of meaningful and unique features using Adaptive time-frequency distribution (TFD) and nonnegative matrix factorization (NMF). We construct Adaptive TFD as an effective signal analysis domain to dynamically track the nonstationarity in the speech and utilize NMF as a matrix decomposition (MD) technique to quantify the constructed TFD. The proposed method extracts meaningful and unique features from the joint TFD of the speech, and automatically identifies and measures the abnormality of the signal. Depending on the abnormality measure of each signal, we classify the signal into normal or pathological. The proposed method is applied on the Massachusetts Eye and Ear Infirmary (MEEI) voice disorders database which consists of 161 pathological and 51 normal speakers, and an overall classification accuracy of 98.6% was achieved.
Dynamic Principal Component Analysis with Nonoverlapping Moving Window and Its Applications to Epileptic EEG Classification
Authors: Xie Shengkun , Krishnan Sridhar
Published: November 2022

Classification of electroencephalography (EEG) is the most useful diagnostic and monitoring procedure for epilepsy study. A reliable algorithm that can be easily implemented is the key to this procedure. In this paper a novel signal feature extraction method based on dynamic principal component analysis and nonoverlapping moving window is proposed. Along with this new technique, two detection methods based on extracted sparse features are applied to deal with signal classification. The obtained results demonstrated that our proposed methodologies are able to differentiate EEGs from controls and interictal for epilepsy diagnosis and to separate EEGs from interictal and ictal for seizure detection. Our approach yields high classification accuracy for both single-channel short-term EEGs and multichannel long-term EEGs. The classification performance of the method is also compared with other state-of-the-art techniques on the same datasets and the effect of signal variability on the presented methods is also studied. 
Latinx Experiences in the Ontario Education System: Race, Invisibility, and Capital
Authors: Parada Henry , Escobar Olivo Veronica , Bravo Fabiola
Published: November 2022

This article explores Latinx youth’s experience in the Ontario education system and the level of support they encounter throughout their education. Based on phenomenological qualitative interviews, this study found that Latinx youth in Ontario lacked sufficient support networks throughout their childhood and adolescence. Using Bourdieu’s theory of capital and education, as well as Latino Critical Race Theory (LatCrit), this research explores how a lack of access to relevant capital positions Latinx youth at a disadvantage in their educational attainment and how their unique experiences are unrecognized. This article is based on a total of 52 participants (27 one-on-one interviews and 23 participants in two focus groups). The findings indicate that youth perceive parents to have limited social networks, skills, and knowledge necessary to assist their children in the Ontario education system. School teachers, guidance counsellors, and principals who are positioned to provide supplemental support for marginalized youth often failed to provide any significant guidance. Youth were faced with finding alternative modes of support or depending entirely on themselves. Given the lack of discourse surrounding the unique experience of the Latinx minority, the experiences of Latinx youth remain mostly unseen.
Signature and Residue Testing of Microprogrammable Control Units
Authors: Geurkov Vadim
Published: November 2022

Arithmetic and algebraic codes are used in testing to verify arithmetic and logical operations performed by digital circuits. An important unit of the hardware that implements arithmetic codes is a residue generator. This is a circuit that generates the residue of a number with respect to a check base. The existing design methods for residue generators are oriented to the special values of the check base. We propose an approach to designing the residue generators with an arbitrary check base. We show how to reduce the probability of error escape, when this type of generator is used for detecting arithmetic errors. We then demonstrate how to embed the designed circuit into a microprogrammable finite state machine to test its operation without adding test hardware overhead. The proposed scheme can be used in arithmetic/algebraic error-control coding and fault-tolerant digital designs. 
Introducing TAM: Time-Based Access Memory
Authors: Mekhiel Nagi
Published: November 2022

 

The increase in processor speed achieved by continuous improvements in technology is causing major obstacles to the parallel processors implemented inside the chip. The time spent in servicing all the cache misses from all processors from a slow shared memory limits the performance gain of parallel processors. We propose a new memory system that makes all of its content available to processors, so that processors need not to access the shared memory in a serial fashion. Rather than having one processor access a single location in the shared memory at a time, we force each location to be available to all processors at a specific time. This new memory system is fast and simple, because it does not need decoders and can use the DRAM or SRAM technology efficiently as the access of each location is known ahead of time. Results show that this new memory improves a single processor performance by 350% and the performance of eight parallel processors by 2400%. The new memory decouples the slow memory from the fast processor and makes the parallel processors scalable to an infinite number of processors.
Closed-Form Analysis of Relay-Based Cognitive Radio Networks Over Nakagami-m Fading Channels
Authors: Hussain Sattar J. , Fernando Xavier
Published: November 2022

We propose a general framework for a comprehensive performance analysis of cooperative spectrum sensing (CSS) in cognitive radio (CR) networks. Specifically, we investigate the detection accuracy of a relay-based CR network over independent nonidentical Nakagami-m fading channels. Based on the probability density function (pdf) approach, we derive new exact and approximated closed-form expressions for the average detection probability and the average false alarm probability employing two diversity combining techniques, namely, the maximal ratio combining (MRC) scheme and the selection combining (SC) scheme. We also investigate the convergence rate of infinite series that appears in the derived exact closed-form expressions and propose to use a powerful acceleration algorithm that allows for the series termination with a finite number of terms. The results obtained reveal the importance of including the relaying link statistics and the combination techniques in the performance analysis of CR networks. The derived closed-form expression can be used to determine the energy threshold and the relaying power constraint that meet a given detection accuracy value over nonidentically distributed Nakagami-mfading.
Novel wireless channels characterization model for underground mines
Authors: Farjow Wisam F. , Raahemifar Kaamran , Fernando Xavier
Published: November 2022

The propagation characteristics of electromagnetic waves in underground mines are different from those in free space because of the harsh underground environment. Physical phenomena like severe reflection, scattering, and diffraction along the mines’ rough walls will affect the propagation of electromagnetic waves. Channel predictions are crucial for reliable and optimal wireless communication in an underground environment. Although there are several channel prediction techniques, most of them are very difficult and time consuming.

This work presents a new approach in wireless channel modeling in underground mines. The model is generated by adopting a performance-based approach rather than

classical coverage-based approach. This new model, called ‘‘Mine Segmenting Wireless Channel Model’’, divides the mine area into three main segments: (1) Line-of-Sight (LOS), (2) Partial-Line-Of-Sight (PLOS) and (3) Non-Line-Of-Sight (NLOS). We examine the impact of topology on performance of 802.11b system with Rician/Rayleigh fading. The model is statistically verified using simulations and is applied to fading wireless local

area networks channel for IEEE 802.11 applications. Finally, the communication performance of a realistic IEEE 802.11b signal is evaluated in a real underground mine gallery (NORCAT Mine, Sudbury, Ontario, Canada). The results of the actual experiment were very similar to that of the model simulation.
Equalization of Multiuser Wireless CDMA Downlink Considering Transmitter Nonlinearity Using Walsh Codes
Authors: Pinter Stephen Z. , Fernando Xavier
Published: November 2022

Transmitter nonlinearity has been a major issue in many scenarios: cellular wireless systems have high power RF amplifier (HPA) nonlinearity at the base station; satellite downlinks have nonlinear TWT amplifiers in the satellite transponder and multipath conditions in the ground station; and radio-over-fiber (ROF) systems consist of a nonlinear optical link followed by a wireless channel. In many cases, the nonlinearity is simply ignored if there is no out-of-band emission. This results in poor BER performance. In this paper we propose a new technique to estimate the linear part of the wireless downlink in the presence of a nonlinearity using Walsh codes; Walsh codes are commonly used in CDMA downlinks. Furthermore, we show that equalizer performance is significantly improved by taking into account the presence of the nonlinearity during channel estimation. This is shown by using a regular decision feedback equalizer (DFE) with both wireless and RF amplifier noise. We perform estimation in a multiuser CDMA communication system where all users transmit their signal simultaneously. Correlation analysis is applied to identify the channel impulse response (CIR) and the derivation of key correlation relationships is shown. A difficulty with using Walsh codes in terms of their correlations (compared to PN sequences) is then presented, as well as a discussion on how to overcome it. Numerical evaluations show a good estimation of the linear system with 54 users in the downlink and a signal-to-noise ratio (SNR) of 25 dB. Bit error rate ( BER) simulations of the proposed identification and equalization algorithms show a BER of 10(-6) achieved at an SNR of similar to 25 dB.

 
The Leaky Feeder, a Reliable Medium for Vehicle to Infrastructure Communications
Authors: Farahneh Hasan , Fernando Xavier
Published: November 2022

Reliable vehicular communications is fast becoming a necessity. Vehicle to infrastructure (V2I) communication, which is critical for safety, is often interrupted when vehicles travel in tunnels. Leaky Feeder (LF) or radiating cable have been the primary solution to provide wireless access in tunnels and mines, but being overlooked until now. The LF is a natural multi antenna transceiver ideal for broadband short rage access. In this work, we model the LF as a linear antenna array and derive the average bit error rate (BER) in Rayleigh fading channel considering Quadrature Phase Shift Keying (QPSK) and M-Array Quadrature Amplitude (M-QAM) Modulations. We consider maximal ratio transmission (MRT) at the transmission end and coherent detection and maximal ratio combining (MRC) at the receiving end. Analytical expressions are derived for the BER. The effects of slot spacing and carrier frequency on the BER are also studied. Numerical evaluations show that the LF is a strong candidate for tunnels with much lower BER than a single antenna transmitter with the same SNR.
An Optimum User Association Algorithm in Heterogeneous 5G Networks Using Standard Deviation of the Load
Authors: Hassan Noha , Fernando Xavier
Published: November 2022

Fifth-generation (5G) wireless networks and beyond will be heterogeneous in nature, with a mixture of macro and micro radio cells. In this scenario where high power macro base stations (MBS) coexist with low power micro base stations (mBS), it is challenging to ensure optimal usage of radio resources to serve users with a multitude of quality of service (QoS) requirements. Typical signal to interference and noise ratio (SINR)-based user allocation protocols unfairly assign more users to the high power MBS, starving mBS. There have been many attempts in the literature to forcefully assign users to mBS with limited success. In this paper, we take a different approach using second order statistics of user data, which is a better indicator of traffic fluctuations. We propose a new algorithm for user association to the appropriate base station (BS) by utilizing the standard deviation of the overall network load. This is done through an exhaustive search of the best user equipment (UE)-BS combinations that provide a global minimum to the standard deviation. This would correspond to the optimum number of UEs assigned to every BS, either macro or micro. We have also derived new expressions for coverage probability and network energy efficiency for analytical performance evaluation. Simulation results prove the validity of our proposed methods to balance the network load, improve data rate, average energy efficiency, and coverage probability with superior performance compared with other algorithms.
Enhancement of Physiological Stress Classification using Psychometric Features
Authors: Magtibay Karl , Fernando Xavier , Umapathy Karthi
Published: November 2022

Psychological data features are underutilized in many acute stress studies since they are challenging to replicate and validate due to their inherent subjectivity. However, psychology and perception play essential roles in stress research according to the well-established allostatic load model. Therefore, we demonstrate the importance of accounting for psychological data in acute stress research in an ambulatory setting through a joint analysis. We enhanced stress classification by combining psychometric features with standard physiological signal features. We used the publicly available Wearable Stress and Affect Database (WESAD), from which we obtained physiological signals and psychological self-assessments from 15 participants. For each participant, a set of physiologically relevant features were extracted from each signal type. In parallel, we adapted psychometric features, positive emotion (PEscore) and negative emotion (NEscore) scores, by calculating the weighted average of self-evaluation scores. Using a stepwise feature selection and a linear-discriminant-analysis-based classifier, we found that PEscore along with select physiological signal features, could enhance cross-validated stress classification accuracy by 8%, higher than a previous benchmark study using the same dataset. More importantly, we found that such a classification accuracy could be achieved with significantly fewer physiological signal features (by 20 times) with the aid of a psychometric feature. Finally, we found that psychometric features could indicate the type of perceived stress relating to an individual's mood descriptor scores. Thus. a combination of psychometric and physiological data could be beneficial towards improving the detection and management of stress and support the development of holistic stress models.

 