Voice Messages Research Articles

A Machine Learning Approach for Air Writing Recognition

Abstract: Air Writing Recognition is a step towards the safety of people. Aim of this project is to make a step towards smart technology and provide an alternative when phones are unable to use. It helps the women, children and citizens in emergency situation. By writing a character (h, p) in air infront of CCTV, it recognizes that someone needs help. This project also send a voice message, text message to get emergency help and support. We hope that this project makes more safety to women, children and citizens and makes the crime rate less. The Air Writing Recognition project is a combination of computer vision object tracking and handwriting recognition. The Air Writing Recognition system uses the webcam of a computer to track character digits written in the air by the user, then uses a optical character recognition(OCR) algorithm to classify the character digits. And further it uses a Twilio account to make calls and sends message depends upon the character that the system recognized

Blind People Helping Hand

Abstract: Blind people are facing many problems in their day-to-day life. They find it very difficult to read books as well as to recognize the object in front of them. From the survey of WHO,30 million peoples are permanently blind and 285 billion peoples with vision impairment. if you notice them, you can very well know about it they can’t walk without the help of other. one has to ask guidance to reach their destination. they have to face more struggles in their life daily life. Visually impaired people find difficulties detecting obstacles in front of them, during walking in the street, which makes it dangerous. A lots of blind people suffer in their own lives because of their vision loss. Vision is one of the five important senses in the human body. People with Vision loss have their own disability. Many countries around the world provide special assistance to these needed people to improve their life quality as good as possible. They provide them with special equipment for their disability to improve their daily life like voice message service, electronic stick that guide them while moving around and other specialized equipment. Blind people can't even walk without any aid. Many times they rely on others for help. Several technologies for the assistance of visually impaired people have been developed. This paper proposes a system for blind people. The proposed system aims to create a wearable visual aid for visually impaired people in which speech commands are accepted by the user. Its functionality addresses the identification of objects .This will help the visually impaired person to manage day-to-day activities through his/her surroundings. To help the blind people the visual world has to be transformed into the audio world with the potential to inform them about objects. Therefore, we propose to aid the visually impaired by introducing a system that is most feasible, compact, and cost effective. So, we implied a system that makes use of Raspberry Pi. Raspberry Pi is used to implement artificial vision using python language on the Open CV platform. The system consists of a webcam interfaced with raspberry pi. Pi Camera detects and find the type of object with the help of ultrasonic sensor. Ultrasonic sensor to detect the real time hurdles while walking on the roads. The ultrasonic sensor used in this project plays a vital role. It detects the object in front of this. When object is detected a indication sound is given to the user via earphone. While they hear this sound they can know an obstacle in front of them. The system is intended to provide Raspberry Pi. The proposed system detects an object around them and sends feedback in the form of speech, warning messages via earphone. This new system may solve some of major problems of blind persons that are still existing. The aim of all these systems is to help the user to detect object without the help of a second person. This system is to provide a low cost and efficient obstacle detection aid for blind which gives a sense of artificial vision by providing information about the environmental scenario of static and dynamic object around them, so that they can walk independently. This paper combines the functionality of Object detection. The objective is to develop user friendly application

Effectiveness and implementation of a text messaging intervention to reduce depression and anxiety symptoms among Latinx and Non-Latinx white users during the COVID-19 pandemic

Text messaging interventions are increasingly used to help people manage depression and anxiety. However, little is known about the effectiveness and implementation of these interventions among U.S. Latinxs, who often face barriers to using mental health tools. The StayWell at Home (StayWell) intervention, a 60-day text messaging program based on cognitive behavioral therapy (CBT), was developed to help adults cope with depressive and anxiety symptoms during the COVID-19 pandemic. StayWell users (n = 398) received daily mood inquiries and automated skills-based text messages delivering CBT-informed coping strategies from an investigator-generated message bank. We conduct a Hybrid Type 1 mixed-methods study to compare the effectiveness and implementation of StayWell for Latinx and Non-Latinx White (NLW) adults using the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework. Effectiveness was measured using the PHQ-8 depression and GAD-7 anxiety scales, assessed before starting and after completing StayWell. Guided by RE-AIM, we conducted a thematic text analysis of responses to an open-ended question about user experiences to help contextualize quantitative findings. Approximately 65.8% (n = 262) of StayWell users completed pre-and-post surveys. On average, depressive (−1.48, p = 0.001) and anxiety (−1.38, p = 0.001) symptoms decreased from pre-to-post StayWell. Compared to NLW users (n = 192), Latinx users (n = 70) reported an additional −1.45 point (p < 0.05) decline in depressive symptoms, adjusting for demographics. Although Latinxs reported StayWell as relatively less useable (76.8 vs. 83.9, p = 0.001) than NLWs, they were more interested in continuing the program (7.5 vs. 6.2 out of 10, p = 0.001) and recommending it to a family member/friend (7.8 vs. 7.0 out of 10, p = 0.01). Based on the thematic analysis, both Latinx and NLW users enjoyed responding to mood inquiries and sought bi-directional, personalized text messages and texts with links to more information to resources. Only NLW users stated that StayWell provided no new information than they already knew from therapy or other sources. In contrast, Latinx users suggested that engagement with a behavioral provider through text or support groups would be beneficial, highlighting this group's unmet need for behavioral health care. mHealth interventions like StayWell are well-positioned to address population-level disparities by serving those with the greatest unmet needs if they are culturally adapted and actively disseminated to marginalized groups. Trial registrationClinicalTrials.gov Identifier: NCT04473599.

Digital Health Technologies for Maternal and Child Health in Africa and Other Low- and Middle-Income Countries: Cross-disciplinary Scoping Review With Stakeholder Consultation

Maternal and child health (MCH) is a global health concern, especially impacting low- and middle-income countries (LMIC). Digital health technologies are creating opportunities to address the social determinants of MCH by facilitating access to information and providing other forms of support throughout the maternity journey. Previous reviews in different disciplines have synthesized digital health intervention outcomes in LMIC. However, contributions in this space are scattered across publications in different disciplines and lack coherence in what digital MCH means across fields. This cross-disciplinary scoping review synthesized the existing published literature in 3 major disciplines on the use of digital health interventions for MCH in LMIC, with a particular focus on sub-Saharan Africa. We conducted a scoping review using the 6-stage framework by Arksey and O'Malley across 3 disciplines, including public health, social sciences applied to health, and human-computer interaction research in health care. We searched the following databases: Scopus, PubMed, Google Scholar, ACM Digital Library, IEEE Xplore, Web of Science, and PLOS. A stakeholder consultation was undertaken to inform and validate the review. During the search, 284 peer-reviewed articles were identified. After removing 41 duplicates, 141 articles met our inclusion criteria: 34 from social sciences applied to health, 58 from public health, and 49 from human-computer interaction research in health care. These articles were then tagged (labeled) by 3 researchers using a custom data extraction framework to obtain the findings. First, the scope of digital MCH was found to target health education (eg, breastfeeding and child nutrition), care and follow-up of health service use (to support community health workers), maternal mental health, and nutritional and health outcomes. These interventions included mobile apps, SMS text messaging, voice messaging, web-based applications, social media, movies and videos, and wearable or sensor-based devices. Second, we highlight key challenges: little attention has been given to understanding the lived experiences of the communities; key role players (eg, fathers, grandparents, and other family members) are often excluded; and many studies are designed considering nuclear families that do not represent the family structures of the local cultures. Digital MCH has shown steady growth in Africa and other LMIC settings. Unfortunately, the role of the community was negligible, as these interventions often do not include communities early and inclusively enough in the design process. We highlight key opportunities and sociotechnical challenges for digital MCH in LMIC, such as more affordable mobile data; better access to smartphones and wearable technologies; and the rise of custom-developed, culturally appropriate apps that are more suited to low-literacy users. We also focus on barriers such as an overreliance on text-based communications and the difficulty of MCH research and design to inform and translate into policy.

CGA-MGAN: Metric GAN Based on Convolution-Augmented Gated Attention for Speech Enhancement

In recent years, neural networks based on attention mechanisms have seen increasingly use in speech recognition, separation, and enhancement, as well as other fields. In particular, the convolution-augmented transformer has performed well, as it can combine the advantages of convolution and self-attention. Recently, the gated attention unit (GAU) was proposed. Compared with traditional multi-head self-attention, approaches with GAU are effective and computationally efficient. In this CGA-MGAN: MetricGAN based on Convolution-augmented Gated Attention for Speech Enhancement, we propose a network for speech enhancement called CGA-MGAN, a kind of MetricGAN based on convolution-augmented gated attention. CGA-MGAN captures local and global correlations in speech signals at the same time by fusing convolution and gated attention units. Experiments on Voice Bank + DEMAND show that our proposed CGA-MGAN model achieves excellent performance (3.47 PESQ, 0.96 STOI, and 11.09 dB SSNR) with a relatively small model size (1.14 M).

Automated Computer Vision System for Urine Color Detection

Urine color analysis is one of the most helpful indicators of health status, and any changes in urine color might be a symptom of serious disease, dehydration of the body, or caused by drugs. To get better assistance for urine color detection in the proposed system, a urine color automatic identification has been developed based on computer vision. The proposed system uses a web camera to capture an image in real-time, analyze it, and then classify the color of urine by using the random forest (RF) algorithm and show the result via the Graphical User Interface (GUI). In addition, the proposed system can send the results to the mobile phone of the patient or care provider by using an Arduino microcontroller and GSM module. Moreover, sending a voice message about the color of urine is related to pathological conditions. The results showed that the proposed system has high accuracy (approximately about 97%) in detecting urine color under different light conditions, with low cost, short time, and easy implementation. In the comparison with the current methods the proposed system has maximum accuracy and minimum error rate. This methodology can pave the way for an additional case study in medical applications, particularly in diagnosis, and patient health monitoring.

TS-CGANet: A Two-Stage Complex and Real Dual-Path Sub-Band Fusion Network for Full-Band Speech Enhancement

Speech enhancement based on deep neural networks faces difficulties, as modeling more frequency bands can lead to a decrease in the resolution of low-frequency bands and increase the computational complexity. Previously, we proposed a convolution-augmented gated attention unit (CGAU), which captured local and global correlation in speech signals through the fusion of the convolution and gated attention unit. In this paper, we further improved the CGAU, and proposed a two-stage complex and real dual-path sub-band fusion network for full-band speech enhancement called TS-CGANet. Specifically, we proposed a dual-path CGA network to enhance low-band (0–8 kHz) speech signals. In the medium band (8–16 kHz) and high band (16–24 kHz), noise suppression is only performed in the magnitude domain. The Voice Bank+DEMAND dataset was used to conduct experiments on the proposed TS-CGANet, which consistently outperformed state-of-the-art full-band baselines, as evidenced by the results.

Low-Cost Technology-Aided Programs for Supporting People With Motor, Visual, and Intellectual Disabilities in Functional Forms of Occupation and Communication: Proof-of-Concept Study.

People with motor, visual, and intellectual disabilities may have serious problems in independently accessing various forms of functional daily occupation and communication. The study was aimed at developing and assessing new, low-cost technology-aided programs to help people with motor or visual-motor and intellectual disabilities independently engage in functional forms of occupation and communication with distant partners. Two programs were set up using a smartphone interfaced with a 2-switch device and a tablet interfaced with 2 pressure sensors, respectively. Single-subject research designs were used to assess (1) the first program with 2 participants who were blind, had moderate hand control, and were interested in communicating with distant partners through voice messages; and (2) the second program with 2 participants who possessed functional vision, had no or poor hand control, and were interested in communicating with their partners through video calls. Both programs also supported 2 forms of occupational engagement, that is, choosing and accessing preferred leisure events consisting of songs and music videos, and listening to brief stories about relevant daily topics and answering questions related to those stories. During the baseline phase (when only a conventional smartphone or tablet was available), 2 participants managed sporadic access to leisure or leisure and communication events. The other 2 participants did not show any independent leisure or communication engagement. During the intervention (when the technology-aided programs were used), all participants managed to independently engage in multiple leisure and communication events throughout the sessions and to listen to stories and answer story-related questions. The findings, which need to be interpreted with caution given the nature of the study and the small number of participants, seem to suggest that the new programs may be viable tools for helping people with motor or visual-motor and intellectual disabilities independently access leisure, communication, and other forms of functional engagement.

The genesis of electronic messages as evidence in civil proceedings

The article is devoted to the question of the genesis of electronic messages as evidence in civil proceedings, in particular, the historical and legal analysis of the introduction of electronic correspondence in the territory of Ukraine and their legal evolution from a means of communication to an independent means of proof.&#x0D; The article analyzes the concept of "electronic communication", a component of which is electronic correspondence. The main approaches to the interpretation of the concept of "electronic message" in regulatory and legal acts and scientific and technical literature were studied, the analysis of the distinction between the generalized concept of "electronic message" and "text, multimedia and voice messages", which is enshrined in the Civil Procedure Code of Ukraine, was carried out. The main features of an electronic message are highlighted: it contains information (certain information and/or data), has an electronic (digital) form, is transmitted using technical means of communication.&#x0D; The stages of the scientific and technical evolution of the Internet and mobile communications as the main channels of electronic communication are studied, and the statistics of their distribution in the world and Ukraine are given. The historical prerequisites for the emergence and development of the main environments for the functioning of electronic messages are characterized: sms-messages, e-mail, social networks and messengers.&#x0D; The evolution of scientific and legal positions regarding the use of electronic correspondence as an evidential basis in civil proceedings from the moment of its emergence as a method of communication to its legal consolidation as a means of proof was studied, in particular, the stages of adaptation of the legal framework and judicial practice in Ukraine were characterized.&#x0D; The current state and problems of using electronic messages as evidence in civil proceedings are characterized. The problematic aspect of using an electronic signature for recording electronic messages and the corresponding distinction between "electronic message" and "electronic document" were studied. The modern trends of changing the judicial paradigm to the principle of self-identification of the author, the presumption of integrity (authenticity) of the evidence, the use of the "letter in response" doctrine and the increase in the legal and evidentiary value of metadata, which will improve the dynamics of using electronic messages as evidence in civil proceedings, have been recorded.

Persuading managers to enact ideas in organizations: The role of voice message quality, peer endorsement, and peer opposition

SummaryWe extend research on employee voice by examining what persuades managers to enact voice messages communicated on organizations' idea management platforms (i.e., software systems designed to gather, vet, and enact employee voice). Applying the elaboration likelihood model of persuasion, we propose that voice message quality affects managerial voice enactment via peer endorsement and that peer opposition qualifies the latter effect. Specifically, we argue that peers are more likely to endorse higher‐ versus lower‐quality voice messages because they are attentive recipients who are motivated to support higher‐quality voice. In turn, we argue that managers are influenced by image concerns and legitimacy inferred by social proof, and thus, they will enact voice messages with higher levels of peer endorsement, especially when combined with lower opposition. Results of our archival analysis of over 5000 voice messages communicated on five organizations' idea management platforms support our predictions, such that peer endorsement mediates the relationship between voice message quality and managerial voice enactment, and that this relationship is stronger under conditions of lower versus higher peer opposition. Altogether, our research illuminates how voice messages on idea management platforms are endorsed and ultimately enacted by organizational leaders.

Faktor Pendukung Dan Faktor Penghambat Pembelajaran Daring Sekolah Dasar Berbasis Whatsapp di Kelas III

The background of this research is the curiosity of researchers about the Supporting Factors and Inhibiting Factors of Whatsapp-Based Online Learning in Theme 2 Class III SDN 009 Sungai Pagar, Kampar Kiri Hilir District, Kampar Regency, and how to provide solutions to the obstacles that arise in online learning. Online learning can be defined as an effort to connect students with learning resources that are physically separate or even far apart but can communicate, interact or collaborate directly and indirectly with each other. This research is a descriptive research using a qualitative approach to field research. The sampling technique used in this research is purposive sampling and snowball sampling while the data collection tools used are observation, interviews and documentation. The research results obtained in the form of whatsapp-based online learning support factors are; The internet/whatsapp can load and send various learning materials such as explanatory videos, picture messages, and voice messages, can communicate and give learning instructions at any time, students can follow learning from anywhere without having to go to school. The inhibiting factors for whatsapp-based online learning are; quota or data package that runs out quickly, signal is not good, also doesn't have an android cellphone. Based on the conclusions above, the researcher submits some suggestions as follows: For class III teachers at SDN 009 Sungai Pagar to reduce the assignments given to students so that assignments do not pile up or continue to give assignments but in small quantities, while students who do not or do not understand the teacher can make visits to students' homes either individually or in groups, For parents of students to be involved in supervising students during online learning because this plays an important role in the success of online learning, For schools to prepare teams of teachers who are on standby at school to help students who have difficulty in learning

The yin and yang of employee voice: an exploratory study

PurposeThis study examines the yin (promotive) and yang (prohibitive) of employee voice based on employee preference for voice channel attributes. Employee inputs may be disregarded, requiring employees to maneuver for unheeded voice and adopt alternate voice tactics. The authors emphasize the ubiquity of lurking employee silence and its affective effects on subsequent cycles of voice or silence.Design/methodology/approachQualitative design involving semi-structured interviews of employees from service sector firms in India assisted the inquiry.FindingsEmployees prefer voice channel attributes that ensure visibility and data substance for promotive voice and anonymity and confidentiality for prohibitive voice. Voice target switching and message reframing were common employee strategies. Silence on both sharing views/opinions (promotive) and voicing issues/concerns (prohibitive) weakens employee future voice incidents, besides suppressing the affect. Post-silence cognitive reappraisal increases voice incidences.Research limitations/implicationsFindings may have limited generalizability given the qualitative design of the study. Moving beyond extant episodic voice research, the authors demonstrate the recurrent nature of employee voice and silence. The study broadens perspectives on how varied voice types necessitate nuanced voice channel attributes.Originality/valuePresent work brings together organizational behavior (OB) perspective on discretionary voice through human resource (HR)-based channels, helping bridge the gap between previously disparate stands.

Social Media as Mobile Learning Oral Chat-Based Constructive Communication to Improve Speaking Skills

WhatsApp is one of the most practical, cost-effective, and communicative mobile applications for college students to enhance their speaking skills. This study reconciled to consuetude college students to flexible habitual use of the English language learning and intended to improve their speaking abilities with specially tailored learning resources and activities aid known as WhatsApp-based speaking instructional material (WABSIM). This exploratory mixed-methods research evaluated oral chat-based utilization of WhatsApp by twenty-eight students for one semester using audio voice messages and video recordings of communicative activities in pairs or groups, dialogues, and interviews activities recorded in the WhatsApp group managed to produce every day classroom and noncollegiate activities. Speaking test consisted of an oral evaluation of student's fluency, vocabulary used, grammar, pronunciation, and comprehensibility aspects. It reveals that students demonstrated a stupendous developing speaking interest in building English sentences by raising questions and delivering responses, improved learning collaboration, created better learning engagement, increased learning self-awareness, and accelerated flexible communication. Besides, students achieved substantial academic progress astoundingly in a semester. Therefore, to emerge the significance acknowledged from this current study, in the current era of mobile technology advancement supporting teaching and learning English, WhatsApp oral chat-based assistance offering teaching and learning English flexibility is the most effective.

Reduced Diarrhea Prevalence and Improvements in Handwashing with Soap and Stored Drinking Water Quality Associated with Diarrheal Disease Awareness Measured by Interactive Voice Response Messages in the CHoBI7 Mobile Health Program.

The Cholera-Hospital-Based-Intervention-for-7-Days (CHoBI7) mobile health program promotes water, sanitation, and hygiene (WASH) behaviors through interactive voice response (IVR), voice, and text messages to reduce diarrheal diseases in Bangladesh. The objective of this study was to investigate the relationship between responses to CHoBI7 WASH IVR quiz messages and subsequent diarrhea and WASH behaviors. Fourteen CHoBI7 IVR quiz messages on handwashing with soap and treatment of stored water were sent to 517 households with 1,777 participants during the 12-month program period. IVR message responses were classified as correct answer, incorrect answer, no response (did not press 1 or 2), and failed (did not answer the phone). Diarrhea prevalence was assessed through self-reported monthly clinical surveillance visits. Handwashing with soap was assessed by a 5-hour structured observation, and stored water quality was defined by Escherichia coli concentration. Households that responded correctly to a CHoBI7 IVR quiz message had significantly lower odds of diarrhea for all age groups (adults and children) at the subsequent visit 1 month later (odds ratio [OR], 0.73; 95% CI, 0.54-0.98), and significantly greater odds of handwashing with soap after stool-related events (OR, 2.48; 95% CI, 1.12-5.49) and E. coli levels < 100 colony forming units (CFU)/100 mL (World Health Organization high-risk cutoff) in the stored household water (OR, 2.04; 95% CI, 1.25-3.33) compared with households that did not answer CHoBI7 IVR quiz calls. Correct responses to CHoBI7 IVR quizzes were associated with decreased diarrhea prevalence and improved stored drinking water quality and handwashing with soap behaviors at the subsequent visits. These findings suggest engagement in the CHoBI7 mobile health (mHealth) program and awareness of diarrheal disease prevention can reduce diarrhea and facilitate changes in WASH behaviors.

Cost analysis of COVID-19 test result notification using an automated messaging system compared to a staff caller practice in Alberta.

In Alberta, polymerase chain reaction (PCR) COVID-19 tests were an important step in detecting and isolating contagious individuals throughout the pandemic. Initially, a staff member provided results to all PCR COVID-19 test clients by phone. As the number of tests increased, new approaches were essential for timely result notification. An innovative automated IT system was introduced during the pandemic to reduce workloads and support timely result notification. At the time of the COVID-19 test booking and again following swabbing, clients had an option to consent to receive their test results via an automated text or voice message. Prior to implementation, a privacy impact assessment was approved, a pilot was undertaken, and changes to lab information systems were made. Health administration data were used in a cost analysis to compare the unique costs associated with the novel automated IT practice (e.g., administration, integration, messages, staffing costs) and a hypothetical staff caller practice (e.g., administration, staffing costs) for negative test results. The costs of sharing 2,161,605 negative test results in 2021 were assessed. The automated IT practice demonstrated a cost savings of $6,272,495 over the staff caller practice. A follow-up analysis determined the cost savings threshold of 46,463 negative tests to break even. Using an automated IT practice for consenting clients can be a cost-effective approach to reach clients in a timely manner during a pandemic or other instances warranting direct notification. This approach is being explored for test result notification of other communicable diseases in other contexts.

Mobile phone aided reminder to promote childhood vaccination: a bibliometric analysis

Background: Vaccines have been demonstrated to reduce the incidence of disease. With global and regional guidance, the World Health Organization provides information and assistance to immunization programs worldwide. Despite all of the efforts, some countries’ vaccination rates remain low. When reminder and recall strategies are employed, vaccination rates in youngsters have been proven to improve. Only a few studies have looked into the effect of reminders sent through mobile phones on vaccine uptake. Objectives and methods: This study aims to evaluate how successful mobile phone-assisted reminders are at improving vaccination uptake rates. For this research, Pub Med, Scopus, Science Direct, and Google Scholar were used to look for papers published in the previous ten years that looked at the effectiveness of mobile phone vaccine reminders for children. These databases’ papers were chosen, extracted, and assessed using the inclusion and exclusion criteria. Out of a total of 1016 articles, ten were chosen for review. Results: According to the chosen articles, the majority of the study involved randomized control trials in both rural and urban settings spanning Africa, Asia, America, and Australia. Most of the research used text message/SMS interventions rather than voice call or phone call treatments. The outcome was determined by appointment adherence, vaccine coverage, and regular immunization completion. Regardless of the type of intervention utilized, the study group had higher vaccination coverage and completion rates than the control groups. In terms of vaccine timeliness, the research groups demonstrated an improvement. Extra incentives, manual calendars, and training have all been shown to be more successful. Providing extra incentives, manual calendars, or training is a more successful means of improving outcomes. Conclusion: Immunization coverage, schedule compliance, and vaccine uptake timeliness have all been proven to improve using mobile phone-assisted reminders in the form of text messages, voice messages, or phone calls. When used in conjunction with incentives, calendars, and training, these reminders help to increase success rates.

Usability of telehealth among healthcare providers during COVID-19 pandemic in Nineveh Governorate, Iraq

ObjectivesTo identify the usability of telehealth services and barriers during the coronavirus disease (COVID-19) pandemic among healthcare providers in Nineveh Governorate-Iraq. Study designThis was a multicenter cross-sectional survey. MethodsWe collected the required data from April to July 2022 using self-administered open-ended questionnaires. The healthcare providers were physicians, pharmacists, and nurses with at least six months of services at hospitals. A modified form of the Telehealth Usability Questionnaire (TUQ) was used to assess the usability of telehealth services. ResultsThere were 460 healthcare providers, of which 269/460 (58.5%) were users of telehealth services. These were mostly physicians (n = 167/269, 62.1%), nurses (52/269, 19.3%), and pharmacists (n = 50/269, 18.6%), with a p-value of 0.001. During the COVID-19 pandemic, physicians (n = 100/167, 60.0%) and pharmacists (n = 28/50, 56.0%) increased their provision of telehealth services. Approximately 60% of physicians and nurses preferred to provide telehealth services in a synchronized manner. The participants mostly used smartphones to provide telehealth services through Messenger/Facebook and WhatsApp applications, specifically utilizing voice and/or video messages. There was some agreement among the participants (n = 269) regarding the usability of telehealth services. The overall mean score (±SD) was 4.8 (±0.88). The most reported barriers to telehealth services were poor Internet services, the presence of specific diseases, lack of technical comprehension, and insufficient time allocated to the service. ConclusionHealthcare providers demonstrated a tendency towards the usability of telehealth services. Despite the available barriers, triage collaborations among patients, healthcare providers, and healthcare institutions are needed to achieve more successful adoption of these services.

Joint uplink–downlink resource allocation for energy efficient D2D underlaying cellular networks with many-to-one matching

Energy efficiency (EE) is an important parameter for the next generation cellular communications which is not limited to voice and text messages only. Device-to-Device (D2D) communication is being viewed as a promising technology to support heterogeneous applications involved in future cellular networks. Due to its short range communication, less amount of power is sufficient to make a successful transmission. By exploiting this feature of D2D, this paper proposes an energy-efficient resource allocation scheme for joint uplink/downlink (UL/DL) D2D considering many-to-one matching criterion for channel reuse among users. In this paper, total EE of D2D pairs (DPs) is taken as a performance metric to be optimized subject to quality of service (QoS) satisfaction for cellular users (CUs) within the power budgets of all the users. An iterative scheme is designed for joint channel and power optimization problem. Simulation results show the convergence of joint iterative algorithm and verify significant performance improvement over other schemes.

The efficacy of Raspberry Pi-based automatic voice message education on knowledge level and prevention behavior of high-risk population

Introduction: The number of confirmed COVID-19 cases has increased in Indonesia. Preventive measures are believed to break the chain of transmission of COVID-19. Therefore, increasing knowledge through health education is essential to improve preventive behavior in the community. The study aims to determine the efficacy of implementing health education using Raspberry Pi based automatic voice massages in increasing high risk populations’ knowledge and prevention behavior.&#x0D; Design and Methods: This study was a quasi-interventional method with a pre-posttest research design and a non-equivalent control group, consisting of 30 respondents in each group. Control group received health education through leaflet sharing, while intervention group received health education through Raspberry-pi based automatic voice massages.&#x0D; Results: This study showed that there were no significant different in knowledge between control and intervention group after obtaining health education. Meanwhile, the intervention group showed higher score in knowledge regarding COVID-19. Moreover, the prevention behavior was significantly improved in both groups after acquiring health education through leaflets and automatic voice messages.&#x0D; Conclusions: Health education using Raspberry Pi based automatic voice messages improved both knowledge and preventive behavior regarding COVID 19 in high risk population.

An investigation of machine learning techniques in speech emotion recognition

&lt;span lang="EN-US"&gt;The natural languages are medium of communication from the inception of civilization. As the technology improves, the text messages, voice messages and videos are the addons in medium of communication. In long distance communication, the analysis of expression is modern area of research. The parameters of assessment are subjective hence the emotion recognition is challenging task. This article furnishes the investigation of various machine learning techniques and novel methods for speech emotion recognition (SER) to determine the feeling/sentiments in a speech. Here, we investigate the three machine learning methods named multinominal Naive Bayes (MNB), logistic regression (LR), and linear support vector machine (LSVM). Further, these techniques are incorporated with the proposed method. The performance of these machine learning techniques is investigated on two different datasets. The datasets consist of voice and text data samples. The prosed method is trained and tested on these datasets. As per the experimentation, it has been observed that the LSVM has outperformed the other two machine learning techniques.&lt;/span&gt;