People's Production Research Articles

Design and Implementation of a Battery Temperature Display System Built on the MC9S12XS128 Platform

With the rapid development of society, people's awareness of environmental protection is becoming stronger and stronger. Due to the greater demand for energy, new energy has become the object of attention. Now electric energy is widely used in all aspects of people's production and life. As a kind of device to store electric energy, battery has been paid more and more attention. How to extend the battery life and ensure the normal and stable operation of the battery has become the focus of research. This design carries on the analysis to the battery, uses the MC9S12XS128 single chip microcomputer. The hardware design and software design of the single-chip microcomputer complete the collection and display of the battery temperature parameters, so as to grasp the performance parameters of the battery, After debugging the display system, the results show that the battery temperature display system can display the temperature status in real time, meeting the working requirements. The system can intuitively understand and master the working status of the battery. So that the battery can work safely and stably.

Pelatihan Pemanfaatan Limbah Plastik Menjadi Produk Kerajinan Tangan Bernilai Ekonomis di Tim PKK RT 001 RW 008 Dusun Pulau Sialang Kampar

This training activity on the use of plastic waste into economically valuable handicraft products is a community service program which aims to provide solutions to the problem of managing plastic waste in the community. The main problem faced is the low level of utilization of plastic waste which has the potential to pollute the environment. This training was carried out with the aim that members of the PKK Team RT 001 RW 008 Dusun Pulau Sialang, Kampar, could understand and practice processing plastic waste into handicraft products such as bags, flower vases and home decorations. These products not only have aesthetic value but also economic value, so they can increase people's productivity and financial independence. In addition, this activity is expected to contribute to reducing the volume of plastic waste that ends up in final disposal sites (TPA). Through this training, participants also gain additional knowledge and skills in managing plastic waste, especially used packaging waste such as plastic bags, drink bottles and detergent packaging, into creative and innovative products. Thus, this activity is able to have a positive impact both economically and environmentally for the people of Sialang Island Hamlet.

Empowerment of Young Entrepreneurs Based on Majelis Ta'lim in Neroktog Village Through Design, Screen Printing, and Digital Marketing Training

Purpose: This community service program aims to empower young people by promoting entrepreneurship and enhancing their skills, particularly in response to high unemployment and the economic impact of the COVID-19 pandemic. The goal is to produce young entrepreneurs who can drive local economic growth.Method: The program includes seminars, workshops, and mentorship in digital marketing, product branding, and entrepreneurial management. It follows a structured process from planning to evaluation, with pre- and post-assessments to measure participant progress.Practical Applications: The program equips participants with skills to leverage digital platforms for business growth, helping them address unemployment and social issues by becoming self-reliant entrepreneurs.Conclusion: The program shows that building entrepreneurial and digital marketing skills boosts young people's productivity and economic potential, contributing to local development and addressing social challenges.

Environmental triggers and future risk of developing autoimmune diseases: Molecular mechanism and network toxicology analysis of bisphenol A

Bisphenol A (BPA), a chemical compound in plastics and resins, widely exist in people's production and life which have great potential to damage human and animal health. It has been proved that BPA could affect human immune function and promote the occurrence and development of autoimmune diseases (ADs). However, the mechanism and pathophysiology remain unknown. Therefore, this study aims to advance network toxicology strategies to efficiently investigate the putative toxicity and underlying molecular mechanisms of environmental pollutants, focusing on ADs induced by BPA exposure. Leveraging databases including ChEMBL, STITCH, SwissTargetPrediction, GeneCards, and OMIM, we identified potential targets associated with BPA exposure and ADs, including rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), multiple sclerosis (MS), Hashimoto's thyroiditis (HT), inflammatory bowel disease (IBD), and type 1 diabetes (T1D). Subsequent refinement using STRING and Cytoscape software highlighted core targets respectively, and Metascape was utilized for enrichment analysis. Gene expression data from the GEO database revealed the upregulation or downregulation of these targets across these ADs. Molecular docking performed with Autodock confirmed robust binding between BPA and core targets, notably PPARG, CTNNB1, ESR1, EGFR, SRC, and CCND1. These findings suggest that BPA exposure may serve as an environmental trigger in the development of autoimmunity, underscoring potential environmental risk factors for the onset of autoimmune conditions.

DPD (DePression Detection) Net: a deep neural network for multimodal depression detection.

Depression is one of the most prevalent mental conditions which could impair people's productivity and lead to severe consequences. The diagnosis of this disease is complex as it often relies on a physician's subjective interview-based screening. The aim of our work is to propose deep learning models for automatic depression detection by using different data modalities, which could assist in the diagnosis of depression. Current works on automatic depression detection mostly are tested on a single dataset, which might lack robustness, flexibility and scalability. To alleviate this problem, we design a novel Graph Neural Network-enhanced Transformer model named DePressionDetect Net (DPD Net) that leverages textual, audio and visual features and can work under two different application settings: the clinical setting and the social media setting. The model consists of a unimodal encoder module for encoding single modality, a multimodal encoder module for integrating the multimodal information, and a detection module for producing the final prediction. We also propose a model named DePressionDetect-with-EEG Net (DPD-E Net) to incorporate Electroencephalography (EEG) signals and speech data for depression detection. Experiments across four benchmark datasets show that DPD Net and DPD-E Net can outperform the state-of-the-art models on three datasets (i.e., E-DAIC dataset, Twitter depression dataset and MODMA dataset), and achieve competitive performance on the fourth one (i.e., D-vlog dataset). Ablation studies demonstrate the advantages of the proposed modules and the effectiveness of combining diverse modalities for automatic depression detection.

Target Signal Communication Detection of Black Flying UAVs Based on Deep Learning Algorithm

Background: Unmanned aerial vehicles (UAVs) are being widely used in many fields, such as national economy, social development, national defense, and security. Currently, the number of registered UAVs in China is far less than that of flying UAVs-the frequent occurrence of unsafe incidents. Objective: The phenomenon of UAVs flying undeclared and unapproved has caused more serious troubles to social public order and people's production and life. Methods: In this paper, to assist the public security department in detecting the phenomenon of UAV black flying, our team conducts a series of research based on the deep learning YOLOv5 (You Only Look Once) algorithm. Results: Firstly, the Vision Transformer mechanism is integrated to enhance the robustness of the model. Secondly, depth-separable convolution is introduced to reduce parameter redundancy. Finally, the SimAM attention-free mechanism and CBAM attention-free mechanism are combined to enhance the attention of small target UAVs. Conclusion: Through the analysis of UAV targets in video surveillance, the rapid identification of black-flying UAVs can be realized, the monitoring and early warning ability of UAVs in a specific area can be improved, and the loss of life and property of people can be reduced or saved as much as possible.

A Review of Deep Learning Based Object Detection Algorithms

With the rapid development of artificial intelligence technology, the traditional manual feature-based object detection method has been gradually replaced by deep learning-based object detection technology. Object detection is the basis and prerequisite for many computer vision tasks aimed at recognizing targets in an image and determining their class and location. The purpose of object detection algorithm research based on deep learning is to improve the detection accuracy and detection speed of the detection algorithm, so that the object detection algorithm can be more safe and convenient applied to People's Daily production and life. This article reviews the evolution of object detection algorithms, focusing on two-stage, one-stage and object detection algorithms based on the transformer architecture. In addition, the performance, advantages and disadvantages of different algorithms are compared, and the development trend of object detection algorithms based on deep learning is summarized in the end.

THE INCREASING INCOME STRATEGY OF SUMBER AGUNG VILLAGE WEST PESIR DISTRICT THAT IMPACT ON COMMUNITY ECONOMY FROM THE PERSPECTIVE OF SIYASAH MALIYAH

The enactment of Law Number 6 of 2014 concerning Villages and Law Number 23 of 2014 concerning Regional Government gives villages the right to regulate their regional affairs. In increasing the village's original income, the village government has the right and authority to widely utilize village wealth. Regarding village income sources, efforts to mobilize resources to develop the people's economic potential will increase people's productivity, so that the productivity of both human resources and natural resources around the people can be increased. In this research study, the formulation of the problem is how the strategy for increasing village original income has an impact on the community's economy and how siyāsah māliyah reviews this strategy. The aim of this research are to find out how the strategy of increasing village original income has an impact on the community's economy and how siyāsah māliyah views this strategy. The type of research used in this research is field research, where this research was carried out by interviewing staff at Sumber Agung Pekon, Ngambur District, Pesisir Barat Regency. Data analysis was carried out qualitatively, processing data analysis using descriptive analysis methods, namely discussions based on general thought patterns and then concluded in specific terms. The research results show that the strategy to increase village original income which has an impact on the community economy in the Sumber Agung area, Ngambur District, Pesisir Barat Regency is by establishing village-owned business entities, developing beach tourism, and also having village markets. The conclusion from the results of this research is that the strategy to increase village original income which has an impact on the economy of the community in the Ngambur area has made a contribution, although not much. Siyāsah māliyah's review of the increase in original village income which has an impact on the economy of the community in the Sumber Agung District of Ngambur is in accordance with the principle of benefit, namely prioritizing the interests of the people rather than the interests of the individual.

Damage Factors and Protection of Low Permeability Reservoir

With the development of science and technology and the progress of society, people's production level has been significantly improved. In this context, people have also put forward higher requirements for the application and development of technology and processes in various production fields. The relevant construction technology of oilfield enterprises is no exception. Low permeability reservoir occupies a large proportion in China's reservoir resources. However, due to the small pore space and large fluid flow resistance of low permeability reservoir, it is more prone to reservoir damage in the development process, and even causes the reservoir to fail to produce in serious cases. Therefore, research on the potential damage factors and damage mechanism of low permeability reservoir and propose corresponding protection strategies are conducive to improving the development effect of low permeability reservoir. The potential damage factors of low permeability reservoir are systematically analyzed, which is of great significance to guide the efficient exploitation of low permeability reservoir.

Effect of argon on classification and identification of organics based on laser‐induced breakdown spectroscopy

AbstractOrganic matter is the material basis of life, which is widely present in people's products and lives. The rapid and accurate detection of organic matter can be applied to the identification of fake and inferior products, the traceability of the origin of agricultural products, and the early warning of explosives in antiterrorism. By combining laser‐induced breakdown spectroscopy (LIBS) with argon, the spectral characteristics of five common organic compounds (nitroglycerin, metronidazole, polyformaldehyde, polypropylene, and phenolic resin), the plasma lifetime, the parameters of plasma thermodynamic state, and the distribution of three existing forms of the element C in two gas environments were compared, the influence of argon on organic LIBS results and the reasons for its enhancement were analyzed. The results indicate that argon makes the atomization of carbon chain structures in organic matter more complete, and reduce the interference of the element N in air on the organic LIBS results to a certain extent. The intensity differences of different organic substances are more obvious. support vector machine optimized by principal component analysis and particle swam optimization algorithm was used to classify five kinds of organic matter. The prediction accuracy of classification in air is 94.4%, and it improves to 100% in argon. This result provides a powerful method for high‐precision, real‐time in‐situ, and rapid identification of organic substances, which has important scientific significance for the study of organic substances LIBS.

ANALYSIS OF POVERTY AS A MAIN PROBLEM OF THE INDONESIAN ECONOMY AND ITS OVERCOME

Poverty is a phenomenon that occurs in almost every developing country. Poverty stems from the inability of some people to organize their lives at a level that is considered humane. The problem of poverty is an unresolved problem in almost every country, including Indonesia. The research method used in this study was a literature study by examining various literature related to the topics discussed. The purpose of this research is to analyze poverty in Indonesia. The results of the analysis show that poverty in Indonesia can be caused by declining standards of global per capita income development, declining work ethic and people's productivity, low levels of education, and limited capital, these conditions reduce the quality of human resources, which leads to decreased productivity. and income. The reason is that the problem of poverty remains a major problem that needs attention and concrete action through the implementation of programs that are both recovery, empowering and facilitative. Therefore, the author wants to analyze poverty in Indonesia along with overcoming economic problems in Indonesia.

Peran Drama Konflik sebagai Strategi Komunikasi Pemasaran pada Akun Elvara

In marketing communication, there are several important aspects that need to be a priority for a businessman, one of which is promotion. Promotion is a strategy carried out by a company to attract and make consumers aware of the products offered. Along with technological advances, business people are now increasingly utilizing e-commerce platforms, such as Tiktokshop, to promote and advertise their products. Tiktokshop also has a live streaming feature whose purpose is to introduce business people's products in detail to consumers directly. Now, one of the Tiktok accounts that uses promotions via live streaming is the Elvara account. Elvara is one of the Tiktok accounts that sells skincare products using a unique marketing communication strategy. Presenting household conflict dramas every day when offering products on live streaming. The purpose of the study was to determine the role of conflict drama as a marketing communication strategy in promoting skincare products offered during live streaming. This study uses a qualitative approach method with the 7P marketing mix theory which includes product, price, place, promotion, people, process, and physical evidence. The results of this study indicate that promotion through conflict drama can influence decision making by loyal consumers (customers) to repeat orders and potential consumers to directly purchase skincare products offered by the Elvara account.

Enabling artificial intelligence‐based scenario application in new type power systems

AbstractAt present, artificial intelligence (AI) technology, as a disruptive and frontier technology, is changing people's production and lifestyle with the cross combination of other scientific fields. Under the background of Green and low‐carbon transition in energy, the construction of new type power systems (NTPS) is the future direction of the transformation and development of the power industry. AI is an important supporting technology for the digital transformation of the power industry, which can accelerate the construction of NTPS and new energy systems. This article provides the author's viewpoints on application of AI technologies in NTPS, mainly involving the development of electric power AI and the main problems it currently faced. The discussion on the bottlenecks of AI application will be focused on data and models. Some future research directions are also presented.

Analisis Strategi Komunikasi Digital Affiliator Pemasaran Fashion dan Beauty di Shopee

This research was conducted to find out the digital communication strategy that Affiliators have in marketing in the field of fashion and beauty on shopping sites on social media Instagram. Shopee is an e-commerce platform that offers online buying and selling transactions safely and reliably via cellphones. Shopee is the object of this research because Shopee has succeeded in marketing digitally to Indonesian consumers, one of which is its Shopee Affiliate program. In this study, we want to examine Affiliators who play a role in promotional activities where someone will sell other people's products and get a commission if a purchase occurs through our reference. This research uses an interview method with 9 active affiliates on Instagram social media. Based on the results of the analysis, there are two most dominant concepts in communication attractiveness, namely Rational and Emotional Attractiveness, while social media influencers have two high source credibility attitudes, namely Attractiveness and Trustworthiness.

Record‐breaking heatwave in North China during the midsummer of 2023

AbstractIn midsummer 2023, a record‐breaking extreme heatwave hit North China, causing significant impacts on people's daily lives and production. This study comprehensively analysed the unique features of this extreme event based on five indices describing the intensity, frequency and impact range. The results show that four of these indices broke the historical record in 2023, and the spatial extent (Tmax >40°C) is the second highest in history. The number of hot days with Tmax >40°C (Tmax >35°C) even reached 23 times (4.2 times) the normal. The combined results of these five indices undoubtedly indicate that this heatwave event is featured by high intensity, long duration, numerous extremely hot days and wide impact range. Furthermore, physical mechanism study revealed that the abnormally warm high‐pressure system persisted in dominating North China, resulting in descending airflow and temperature increases. The enhanced and unprecedented westward extending Western North Pacific Subtropical High, the enhanced and eastward extending Iran Subtropical High and the abnormal high‐pressure over southwestern China form an east–west connected anomalous high‐pressure zone, blocking the water vapour transport from lower latitude oceans to North China. Noticeably, North China has experienced a reduction in precipitation since about 2 months preceding this extreme heatwave, leading to severe soil moisture deficiency and reduced evaporation. Consequently, it increased surface sensible heat flux that led to a rise in temperature. This local land‐atmosphere positive feedback mechanism plays a crucial role in the intensification and maintenance of this extreme heatwave event.

Overcoming cross-language communication barriers with speech recognition technology

The purpose of this study is to explore the use of speech recognition technology in addressing communication and language barriers between individuals from different geographical locations. Through a case study, this paper collects data from a variety of sources to demonstrate the effectiveness of speech recognition technology in enhancing cross-cultural communication. The findings show that speech recognition technology can greatly improve communication, reduce misunderstandings, and ultimately promote understanding and cooperation between individuals from different regions. This technology can help people overcome language barriers and achieve more fluent communication. In addition, speech recognition technology can improve people's productivity as it can quickly convert spoken language into written text.Speech recognition technology also has a wide range of applications in cross-cultural communication. It can be used in various fields such as business, tourism, education and healthcare. By using speech recognition technology, differences between cultures can be better understood and respected, leading to more harmonious social relationships.

PEMODELAN GEOGRAPHICALLY WEIGHTED REGRESSION (GWR) MENGGUNAKAN PEMBOBOT KERNEL PADA KASUS TINGKAT PENGANGGURAN TERBUKA DI KALIMANTAN

AbstractUnemployment is one of the serious problems in Indonesia's economic development. This unemployment describes human resources that have not been utilized optimally, as a result of which people's productivity and income have not been maximized, this can also be one of the causes of poverty and other social problems. This study aims to find out the general picture of the open unemployment rate in the Kalimantan region, get the best model and factors that influence the open unemployment rate and illustrate it through thematic maps. The study began with testing assumptions and spatial effects then continued with testing global regression modeling and Geographically Weighted Regression. The weighting function used in this study is adaptive gaussian kernel. The variable that has a positive effect on the open unemployment rate in the Kalimantan region is population density. While the variable that negatively affects the open unemployment rate is the Labor Force Participation Rate. Keywords: Open Unemployment Rate, Kalimantan Island, Spatial, GWR

From the Perspective of Service and Transformation: How to Develop Small and Medium-Sized Electromechanical Enterprises - Based on "Changzhou Jiutian Electromechanical"

In recent years, with the continuous development of society, the mechanical and electrical industry technology continues to update, so that the mechanical and electrical automation in many fields show multi-function, high efficiency, green environmental protection, and other characteristics, the use of mechanical and electrical equipment in people's life and production of more and more high proportion. Based on this, Liyang City, Jiangsu Province has created a new pattern of "one core park and many bases" with Zhongguancun Science and Technology Industrial Park as the core and the township's characteristic industrial base as the auxiliary. Promoted the development of new industries, new enterprises, and new products, so that Liyang agriculture and animal husbandry machinery and other advanced manufacturing industries rapidly rise. With the fierce competition, the company has gained 65% of the domestic market share, and the 1.2 billion yuan company is working to build a global high-end grain machinery production base, transforming "Made in Europe and America" to "Made in China". How small and medium-sized mechanical and electrical enterprises survive in the fierce competition has triggered thinking. In this case, utilizing field investigation and online interview, the strategic analysis of Changzhou Jiutian Mechanical and Electrical Equipment Co., Ltd TD was conducted using the Porter five force model and Boston matrix analysis. Changzhou Jiutian Mechanical and Electrical Equipment Co., Ltd., as a small and medium-sized electromechanical enterprise, needs to stand firm in the current competitive environment. Our research shows that we should start with the service and transformation strategy to realize the self-development of enterprises.

Pengaruh Infrastruktur terhadap PDRB Kawasan Timur Indonesia Tahun 2014 – 2022

Economic growth according to Solow Swan's theory is influenced by the factors of capital accumulation, labor, and technological progress. Infrastructure is a form of physical capital that can increase economic activity. During the government of President Joko Widodo, there is the concept of “Nawacita” which in its agenda has points to increase people's productivity and competitiveness in the international market and points to build Indonesia from the periphery by strengthening regions and villages within the framework of a unitary state. The real condition that occurs today is the phenomenon of the development gap. In order to implement this agenda, the government divides Indonesia into the Western Region and the Eastern Region of Indonesia. Eastern Indonesia is considered to be underdeveloped because if seen from the contribution of KTI to the National GRDP, it only contributes less than 25 percent. The purpose of this study is how infrastructure affects the 17 provinces of Eastern Indonesia. The study uses secondary data with panel data regression analysis with the Fixed Effect Model (FEM). The variables used are economic growth represented by GRDP as the dependent variable and road infrastructure, electricity infrastructure, TPAK, number of internet users as independent variables. The results showed that the variables of electricity infrastructure and the number of internet users had a significant positive effect on economic growth while the variables of road infrastructure and TPAK had no significant effect on economic growth.

Big Data Trade Survey Pricing, Trading, and Data Protection

In this era, Big Data is considered as the key to unlocking the growth of people's productivity in daily life. Internet usage, mobile applications and social networks, as well as the internet of things based on smart-grid and so on has an impact on the amount of data collected. The advancement of analytics data provided by machine learning and data mining technology supported by cloud computing, the resulting information will be more useful. Since the advent of Big Data, the dataset has become one type of "new money" in the digital world. Copyright protection mechanisms including digital encryption and watermarking need to be done to maintain data values. To maximize this, an effective container is needed to allow data owners and buyers to trade the data. The focus of the topic is on designing data trading platforms and schemes, supporting effective and efficient data trading, security, and maintaining the privacy of data owners.