Search results

Taking instances from extant findings from the literature, the study aims to examine the community perception toward renewable energy (RE) off-grid (mini-grid/microgrid) intervention, the underlying rationales for engagement of communities in RE off-grid projects, the different alternatives/models to engage communities in various phases of RE off-grid project deployment.

The study has followed the structured literature review to explore the identified research question of the study.

Based on findings from the review, the framework for effective community engagement in RE mini-grid projects is suggested. Furthermore, the study also draws suggestions and implications for future research and practice.

Based on such understanding the present study offers the framework which suggests the steps for the engagement of the communities in the off-grid projects. The key steps are managing the perception of the community (including generation of awareness among the community), planning for the benefits of the community, linkage the sustainable development goals (SDG), planning for the inclusion of the community and measuring performance (in the line of social and economic criteria and SDG).

This study finds the gap in the literature on the nexus of community, off-grid energy projects and SDG. Following the findings from the scholars in this field, a few gaps in the policy and practice have been highlighted which could be useful for practitioners and policymakers in this area.

This paper aims to examine the role of bullying victimization in predicting psychopathology, encompassing post-traumatic stress disorder (PTSD), risk of developing prodromal psychosis and emotional and behavioural problems, among in-school Nigerian adolescents.

A total of 351 junior secondary students (n = 173 males, 178 females; age range: 9–17 years) were recruited from five randomly selected public secondary schools in Nigeria. Students completed a variety of self-report measures, including a socio-demographic questionnaire, the prodromal questionnaire – brief version, the strengths and difficulties questionnaire (SDQ) and the multidimensional peer victimization scale. They were also interviewed using the PTSD module of the Mini International Neuropsychiatric Interview-Kid Version.

Although bullying victimization was not found to predict the presence of PTSD, it predicted the risk of developing prodromal psychosis. All SDQ subscales also held significant positive associations with bullying victimization. This indicates that higher levels of victimization are associated with increased behavioural and emotional difficulties among adolescents.

The study findings add support to whole system approaches involving relevant stakeholders in health, education, social and criminal justice sectors via protective policies to address the problems of bullying in schools.

The study contributes to evidence demonstrating a need for improved understanding regarding the role of exposure to bullying victimization in predicting various forms of psychopathology. Furthermore, there is specifically a need for research with this focus in developing countries in sub-Saharan Africa and the Nigerian education system.

The purpose of this paper is the study of the electro-vortex flow (EVF) as well as heating and melting processes for mini industrial direct current electric arc furnace (DC EAF).

A mini DC EAF was designed, manufactured and installed to study the industrial processes of heating and melting a small amount of melt, being 4.6 kg of steel in the case under study. Numerical modelling of metal melting was performed using the enthalpy and porosity approach at equal values and non-equal values of the solidus and liquidus temperatures of the metal. The EVF of the liquid phase of metal was computed using the large eddy simulation model of turbulence. Melt temperature measurements were made using an infrared camera and a probe with a thermocouple sensor. The melt speed was estimated by observing the movement of particles at the top surface of melt.

The thermal flux for metal heating and melting, which is supplied through an arc spot at the top surface of metal, is estimated using the thermal balance of the furnace at melting point. The melting time was estimated using numerical modelling of heating and melting of metal. The process started at room temperature and finished once whole volume of metal was molten. The evolution of the solid/melt phase boundary as well as evolution of EVF patterns of the melt was studied.

Numerical studies of heating and melting processes in metal were performed in the case of intensive liquid phase turbulent circulation due to the Lorentz force in the melt, which results from the interaction of electrical current with a self-magnetic field.

In addition to agriculture, energy production, and industries, potable water plays a significant role in many fields, further increasing the demand for potable water. Purification and desalination play a major role in meeting the need for clean drinking water. Clean water is necessary in different areas, such as agriculture, industry, food industries, energy generation and in everyday chores.

The authors have used the different search engines like Google Scholar, Web of Science, Scopus and PubMed to find the relevant articles and prepared this mini review.

The various stages of water purification include coagulation and flocculation, coagulation, sedimentation and disinfection, which have been discussed in this mini review. Using nanotechnology in wastewater purification plants can minimize the cost of wastewater treatment plants by combining several conventional procedures into a single package.

In society, we need to avail clean water to meet our everyday, industrial and agricultural needs. Purification of grey water can meet the clean water scarcity and make the environment sustainable.

This mini review will encourage the researchers to find out ways in water remediation to meet the need of pure water in our planet and maintain sustainability.

Traditional library book recommendation methods are mainly based on association rules and user profiles. They may help to learn about students' interest in different types of books, e.g., students majoring in science and engineering tend to pay more attention to computer books. Nevertheless, most of them still need to identify users' interests accurately. To solve the problem, the authors propose a novel embedding-driven model called InFo, which refers to users' intrinsic interests and academic preferences to provide personalized library book recommendations.

The authors analyze the characteristics and challenges in real library book recommendations and then propose a method considering feature interactions. Specifically, the authors leverage the attention unit to extract students' preferences for different categories of books from their borrowing history, after which we feed the unit into the Factorization Machine with other context-aware features to learn students' hybrid interests. The authors employ a convolution neural network to extract high-order correlations among feature maps which are obtained by the outer product between feature embeddings.

The authors evaluate the model by conducting experiments on a real-world dataset in one university. The results show that the model outperforms other state-of-the-art methods in terms of two metrics called Recall and NDCG.

It requires a specific data size to prevent overfitting during model training, and the proposed method may face the user/item cold-start challenge.

The embedding-driven book recommendation model could be applied in real libraries to provide valuable recommendations based on readers' preferences.

The proposed method is a practical embedding-driven model that accurately captures diverse user preferences.

Menstruation is a part of the female reproductive cycle that begins with adolescence. Menstruation is a natural change; it relates to several malpractices and misconceptions that may contribute to adverse health outcomes.

The authors have searched relevant papers using Google Scholar and PubMed to write this mini review.

During menstruation, poor hygiene maintenance can cause serious illness, which includes the urinary tract and reproductive tract infection. Menstruation management is a hygienic system, and it is essential for females because poor hygiene maintenance during menstruation can cause some infections and numerous sexually transmitted diseases. There are a few nanotechnology-based products that have come into the market to offer some relief to females during their periods.

This mini review will help researchers to design innovative female hygiene products that can relieve the discomfort caused to women during their reproductive age.

This study presents a systematic literature review (SLR) of the interdisciplinary literature on drones in last-mile delivery (LMD) to extrapolate pertinent insights from and into the logistics management field.

Rooting their analytical categories in the LMD literature, the authors performed a deductive, theory refinement SLR on 307 interdisciplinary journal articles published during 2015–2022 to integrate this emergent phenomenon into the field.

The authors derived the potentials, challenges and solutions of drone deliveries in relation to 12 LMD criteria dispersed across four stakeholder groups: senders, receivers, regulators and societies. Relationships between these criteria were also identified.

This review contributes to logistics management by offering a current, nuanced and multifaceted discussion of drones' potential to improve the LMD process together with the challenges and solutions involved.

The authors provide logistics managers with a holistic roadmap to help them make informed decisions about adopting drones in their delivery systems. Regulators and society members also gain insights into the prospects, requirements and repercussions of drone deliveries.

This is one of the first SLRs on drone applications in LMD from a logistics management perspective.

The aim of this study is to understand how digital platforms and context-specific characteristics of China – such as swift guanxi – affect opportunities for small and medium enterprises (SMEs) entering this market.

This study adopts a qualitative approach based on a multiple-case study of Italian SMEs in the wine industry that have activated international activities in China. Primary data consist of 32 interviews with SMEs’ managers, local consumers and other stakeholders involved in firm internationalization.

The findings of this study highlight that in SMEs’ internationalization, the process of knowledge/learning on digital platforms takes place in a bidirectional way thanks to the interactions among multiple stakeholders, which activate consumer education and knowledge sharing.

While previous research has emphasized firms' knowledge acquisition in the internationalization process, this study incorporates both the consumer perspective and the firm perspective, along with considering interactions with various stakeholders.

Engineering graduates are expected to have certain attributes in addition to technical expertise that includes development in personal and interpersonal skills with societal concern. Pedagogical strategies have been continuously evolving to improve the graduate attributes. An efficient framework for blended learning that improves the graduate attributes is the need of the hour now.

A blended course model based on TPACK is proposed and the same is evaluated with Kirkpatrick evaluation method to assess the attainment of the attributes. A mapping strategy is developed for the relation between course outcomes and graduate attributes. The proposed model is tested with “Microcontroller” course in undergraduate program with students of three consecutive years in three different learning environments: offline, online and blended. The performance of the students in assessments, students’ feedback and their interest towards additional learning, project skills and job recruitment are the different elements taken for analysis.

The results obtained show that the impact of the proposed blended learning framework in improving the graduate attributes is greater than the offline environments. The analysis is done based on Kirkpatrick evaluation, which demonstrates the improvement in graduate attributes in blended learning by 18% compared to offline mode.

It is seen that blended learning shall be implemented using TPACK model effectively and the proposed model results in improvement of graduate attributes. Though the findings are good enough, the case study is limited to a particular organization and so, the various underlying parameters may vary for different institutions.

The methodology proposed is viable in any institution and may be tested for any program. The effectiveness of the blended learning is known and in this case study, the analysis from the course to the level of program is done.

The research work highlights the integration of technology, pedagogy and content knowledge to enhance engineering students' skills. Hence, it explores a new required norms of education, potentially shaping future teaching learning methodologies. By employing the Kirkpatrick evaluation, it offers insights into the model's effectiveness and influences educational practices in the need of the hour.

The proposed method and results signifies an innovative endeavor that combines technological expertise, pedagogical methods and subject matter knowledge to enhance the attributes of engineering graduates. Kirkpatrick evaluation adds a distinct dimension by objectively assessing the model's impact. The results are analyzed from the original data obtained from a particular institution.

This paper aims to address the safety concerns of path-planning algorithms in dynamic obstacle warehouse environments. It proposes a method that uses improved artificial potential fields (IAPF) as expert knowledge for an improved deep deterministic policy gradient (IDDPG) and designs a hierarchical strategy for robots through obstacle detection methods.

The IAPF algorithm is used as the expert experience of reinforcement learning (RL) to reduce the useless exploration in the early stage of RL training. A strategy-switching mechanism is introduced during training to adapt to various scenarios and overcome challenges related to sparse rewards. Sensor inputs, including light detection and ranging data, are integrated to detect obstacles around waypoints, guiding the robot toward the target point.

Simulation experiments demonstrate that the integrated use of IDDPG and the IAPF method significantly enhances the safety and training efficiency of path planning for mobile robots.

This method enhances safety by applying safety domain judgment rules to improve APF’s security and designing an obstacle detection method for better danger anticipation. It also boosts training efficiency through using IAPF as expert experience for DDPG and the classification storage and sampling design for the RL experience pool. Additionally, adjustments to the actor network’s update frequency expedite convergence.