Distribution Of Services Research Articles

School Counselors' Efforts in Implementing Career Guidance Services

This study aims to determine the roles and responsibilities of school counselors regarding student career services, as well as the form of school counselors' efforts in implementing career guidance services in SMK Al Falah Salatiga. This qualitative phenomenological study involved a school counselor and 39 11th-grade students. Primary and secondary data were collected through observation, interview, and documentation, and analyzed using data reduction, presentation, and conclusions. The study's finding demonstrates that (1) The school counselor's role in career advice services is to identify issues and address them, as well as to identify potentials as informants and career educators, facilitators, determinants, and implementers of career counseling programs. (2) The types of career advice services included: (a) orientation services; and (b) information technology services, which were delivered through websites and WhatsApp groups, power point files, pdf, eBooks, and learning videos; (c) Placement and distribution services, which were done through internship programs to direct students' skills.

Modeling and Simulation of High Voltage Power Lines under Transient and Persistent Faults

The work proposes an original method for modeling and simulating the triggering of 110 kV interconnection power lines in case of common faults, such as transient or persistent faults. Urban and industrial areas, surrounding urban areas, require a high energy consumption that is being supplied through 110 kV overhead power lines, responsible for distributing power to the industrial and domestic consumers. High voltage distribution power lines are most prone to failure, due to their exposure, affecting a large number of consumers if a fault occurs. Faults of power lines in service certify that currently there is no perfectly controllable operation mode in terms of load rating, environmental factors, insulation resistance, or mechanical resistance, which would allow total avoidance of faults, it is only possible to reduce the impact they have on the network as a whole. Mathematical models have been developed to determine the experimental voltage and current responses describing the fault propagation, expressed as a 7th-degree polynomial curve, as a second-order transfer function or as the Gaussian model type. By comparing these mathematical models, the most probable answers that can lead to the development of a control structure for rapid identification of a fault were obtained, with the possibility of triggering the line protection relay. In the final part of the manuscript, the viability of applying artificial intelligence techniques, for the approached fault management application, is proven. The developed control structure evaluates the nature of the fault and determines a faster reaction of the line protection causing an increase in the performance of the distribution service.

Descriptive Analysis Sociodemography of Breastfeeding Mother in Suku Anak Dalam During Covid-19 Pandemic

Now moment now this the problem of Covid-19 in Indonesia already start sloping however no could denied that mother breastfeed must exists enhancement power stand body especially baby with breastfeeding , breastfeeding becomes very good protection for baby. Effect Breast milk protection is very strong in fighting disease infections through increased power hold on baby. The purpose of this study to determine the characteristics mother breast-feed in Suku Anak Dalam in on period pandemic . Quantitative research methods , design cross-sectional with a total sampling of 58 respondents mother breast-feed in Suku Anak dalam , data collection is done through observation and questionnaire . Results study obtained 98.3% of mothers no work , 58.6% mother no take formal education , 62.1% range age mother reproduction , 77.6% mother have child ≥ 3, 98.3% mother going through a normal childbirth process is not in service health , 94.8% Mother argue that breast milk can replaced with other foods as well as 98.3% mothers provide complementary foods aged <6 months. Concluded description from sociodemography on mother breastfeeding in the tribe child in must very noticed and need maximizing facility and service health especially continuity health on mother and child with maximizing program management lactation , as well with condition moment now this need exists cooperation cross- sector and cross program inside even distribution service excellent health.

Factors Affecting the Punctuality of Logistics Services Using Binary Logistic Regression

The Indian logistics industry is in a period of rapid development. The purpose of this study is to analyze the factors affecting the punctuality of trucks for logistics distribution services in India based on data analysis. The data comes from 6880 pieces of data from the VTS data platform. A binary regression model was established for data analysis, and the model was tested to ensure statistical significance. Binary logistic regression was used to examine truck types, geographic locations, commodity types, order types, and suppliers for logistics services to examine significant differences between on-time and late. Binary logistic regression concluded that the shorter the distance, the signing of the perfect contract, and the selection of a specific type of vehicle, the better development of the logistics level is easier to be on time. This study provides suggestions for improving management strategies, which can be used as a reference for the development of logistics companies.

Public Service Delivery in Nepal: A Case of Passport Distribution from Passport Department, Kathmandu

Public service delivery is providing goods and services to the people. Public service delivery is provided to the people by creating institution, developing system and needs of the people. Government of Nepal (GoN) created different ministries, departments and agencies to provide public services to the citizen. To provide public service delivery GoN created policies, Act, rules and regulations. This study concern to passport distribution service delivery which is systematized through passport act, rules and regulation. Passport are distributed from DoP, 77 districts and 39 diplomatic mission. In the year 2010 to 2021 total number of passport distributed were 7,037,320 citizens in which 22.10 percent of were females, and 77.90 percent of were males. Thus male were more provided service delivery in terms of passport distribution. DoP 2021 showed that, total of 553258 passport were distributed in that year in which 162,954 passport have been applied and distributed from DOP, 298,367 were applied and distributed from the districts, and 91,937 were applied and distributed from the missions abroad. This showed that service delivery at district level are higher.

UPAYA GURU BIMBINGAN DAN KONSELING TERHADAP KASUS PUTUS SEKOLAH SELAMA PANDEMI COVID 19 DI SEKOLAH MENENGAH KEJURUAN PROVINSI KEPULAUAN BANGKA BELITUNG

This paper aims to discuss the Guidance and Counseling Teacher Efforts Against Dropout Cases During the Covid 19 Pandemic at Vocational High Schools in the Bangka Belitung Islands Province, which includes the efforts that have been made by BK teachers in preventing dropout cases during the covid pandemic and the factors that affect children dropping out of school during the covid 19 pandemic. The method used is descriptive qualitative and analyzed with an interactive analysis model by collecting data, reducing data and concluding data. The results of the discussion show that the factors that cause school dropouts during the Covid-19 Pandemic in Vocational High Schools in the Bangka Belitung Islands Province consist of: First, internal factors originating from within the students themselves, namely the lack of motivation to learn in students, and students having difficulty learning online at the time of the Covid-19 pandemic. Second, external factors that come from outside which include the lack of parental support in learning, students working with parents in the plantation and IT sectors, external environmental influences such as online games, and juvenile delinquency, as well as cases of pregnancy outside marriage. and Counseling for dropout cases during the Covid-19 pandemic at Vocational High Schools in the Bangka Belitung Islands Province are through: First, Preventive Efforts, namely by conducting Placement and Distribution Services, Orientation Services, Classical Guidance Services and school involvement. Second, curative efforts, namely by carrying out Home Visit Support Services, Individual Counseling, and Stop Outs.

DDS-XRCE Standard Performance Evaluation of Different Communication Scenarios in IoT Technologies

Although the increasing number of technological products brings many solutions for Internet of Things (IoT) applications, it also causes some drawbacks, such as whether the product in question would run accordingly to a system structured to enable high-performance like Data Distribution Service (DDS). Therefore, the capabilities of the products must be defined to say that they are compatible enough. This paper aims to evaluate the performance of the DDS-XRCE standard while observing its working mechanism. As test scenarios, we benefit from three DDS-XRCE deployments that occurred due to the kind of receiver and sender, the path that packets follow, and the protocols used. Test conditions were set by switching stream modes, transport profiles, and limiting packet deliveries. We obtained the test environment by creating the DDS and DDS-XRCE objects using several eProsima implementations and tools for the standards. We monitored the network messages in two ways: 1) Using multiple Gnome Terminator terminals for observation via the human eye during testing. 2) Using Wireshark to save the information of the packets for further examination. We conducted 36 experiments focusing on latency, throughput, and packet loss. As a result of our study, the DDS-XRCE standard is deemed suitable for Internet of Things applications.

Current Situation and Countermeasures of the Catering Distribution Industry under the O2O Mode

With the help of Internet technology, the catering industry has formed a variety of new marketing modes, which overturned the original catering mode to a large extent. Therefor, the enterprises can choose more effective distribution methods to promote the development of the catering distribution industry. In this context, this work studied the current situation of the catering distribution industry under the O2O mode, analyzed the development situation of the catering O2O market and the catering distribution O2O mode, and articulated the current application situation of the O2O mode in the catering distribution industry. Also, this work analyzed the problems existing in the O2O mode in the catering distribution industry, including the potential risks of food products due to insufficient market supervision, non-standard food distribution and improper handling of after-sales problems. To address the problems, we put forward associated solutions to improve the management system by strictly implementing the catering distribution service standards and building an intelligent system to form a take-out distribution O2O closed loop. This study is expected to provide a guarantee for the sustainable development of the catering industry.

One-Class Convolutional Neural Networks for Water-Level Anomaly Detection.

Companies that own water systems to provide water storage and distribution services always strive to enhance and efficiently distribute water to different places for various purposes. However, these water systems are likely to face problems ranging from leakage to destruction of infrastructures, leading to economic and life losses. Thus, apprehending the nature of abnormalities that may interrupt or aggravate the service or cause the destruction is at the core of their business model. Normally, companies use sensor networks to monitor these systems and record operational data including any fluctuations in water levels considered abnormalities. Detecting abnormalities allows water companies to enhance the service's sustainability, quality, and affordability. This study investigates a 2D-CNN-based method for detecting water-level abnormalities as time-series anomaly pattern detection in the One-Class Classification (OCC) problem. Moreover, since abnormal data are usually scarce or unavailable, we explored a cheap method to generate synthetic temporal data and use them as a target class in addition to the normal data to train the CNN model for feature extraction and classification. These settings allow us to train a model to learn relevant pattern representations of the given classes in a binary classification fashion using cross-entropy loss. The ultimate goal of these investigations is to determine if any 2D-CNN-based model can be trained from scratch or if transfer learning of any pre-trained CNN model can be partially trained and used as the base network for one-class classification. The evaluation of the proposed One-Class CNN and previous approaches have shown that our approach has outperformed several state-of-the-art approaches by a significant margin. Additionally, in this paper, we mention two interesting findings: using synthetic data as the pseudo-class is a promising direction, and transfer learning should be dealt with considering that underfitting can happen because the transferred model is too complicated for training data.

Expanding the accessibility of harm reduction services in the United States: Measuring the impact of an automated harm reduction dispensing machine

BackgroundIn 2021, approximately 107,622 Americans died from drug overdose in the United States. With overdose deaths rising rapidly, it is imperative that prevention efforts focus on expanding proven, evidence-based strategies to curb overdose death rates such as targeted naloxone distribution and syringe service programs (SSPs). The COVID-19 pandemic placed additional strain on SSPs, increasing the need for programs that minimize direct contact and potential COVID-19 exposure. The purpose of this study is to evaluate the impact of an automated harm reduction dispensing machine on the local accessibility of harm reduction services. ObjectivesThe primary outcome of the study is the number of harm reduction supplies distributed to the community by the dispensing machine in its first year compared to the number of supplies distributed by the same organization in the previous year. Secondary outcomes include the countywide incidence of fatal drug overdose and human immunodeficiency virus (HIV) compared to previous years. MethodsThe machine is located outside, in the same location as a once weekly, in-person SSP. Clients register with the program over the phone with a harm reduction coordinator. Each client is connected to products and services such as naloxone, sharps containers, safer injection/smoking kits, pregnancy tests, HIV tests, substance use disorder treatment, and more. ResultsSince installation, 637 individuals registered with the program, 12% of whom had never reportedly used harm reduction services before. Within its first year of use, the machine dispensed 3360 naloxone doses and 10,155 fentanyl test strips, more than any other SSP in the county. ConclusionThe implementation of an automated harm reduction dispensing machine led to an increased accessibility of harm reduction products and services and was associated with a lower countywide incidence of unintentional overdose death and HIV. The association with decreased overdose death and HIV incidence should be further investigated to assess causality.

Restoration model for unbalanced distribution networks considering renewable sources uncertainties

Extreme events cause blackouts, resulting in the distribution network being unable to obtain power from the upstream transmission system. In this situation, local distributed resources can be fully utilized to improve system resilience. A distribution service restoration model is proposed in this paper, where three-phase unbalance condition and renewable sources uncertainty have been considered. The network reconfiguration strategy based on traditional tie switch operation is adopted to isolate faults. To cope with uncertainty, the chance-constrained method is introduced to enable renewable sources to participate in restoration, improving load recovery level. The proposed distribution service restoration model is essentially a mixed-integer nonlinear programming problem (MINLP) with probability constraints. To this end, linearization method is introduced to convert original MINLP into a deterministic mixed-integer linear programming problem. Simulation tests based on IEEE 33-bus network is carried out to demonstrate the feasibility of proposed distribution service restoration model.

A nationwide, cross-sectional, web-based survey on healthcare providers' knowledge about, attitudes toward, and perceived barriers to adherence to clinical practice guidelines for anticancer drug therapy for older patients with cancer in Japan

IntroductionIn July 2019, in accordance with the Medical Information Distribution Service Manual for Guideline Development 2014, which was based on the Grading of Recommendations Assessment, Development and Evaluation approach, the Japanese Society of Medical Oncology (JSMO) and the Japan Society of Clinical Oncology (JSCO) published clinical practice guidelines (CPGs) on chemotherapy and other drug therapies for older patients with cancer (JSMO-JSCO CPGs). In September 2020, at one year after the publication of these guidelines, a survey was conducted to determine the extent to which they had been disseminated to JSMO and JSCO members and implemented in daily practice. Materials and MethodsThis nationwide, cross-sectional, web-based survey was conducted with JSMO and JSCO members. We surveyed the participants' overall awareness of the JSMO-JSCO CPGs, and their knowledge about, attitudes toward, and perceived barriers to adherence to each recommendation using validated questionnaires based on theoretical frameworks used in previous studies (Awareness to Adherence Model, Clinicians' Assessments of Practice Guidelines in Oncology questionnaires, and Knowledge–Attitudes–Behavior Framework). ResultsAmong JSMO and JSCO members who had been informed of the survey, 1230 responded (response rate: 8.6% and 4.8%, respectively). From these respondents, 107 were excluded because they did not practice anticancer drug therapy at the time of the survey. Of the remaining 1123 eligible participants, 674 (60.0%) were aware of the JSMO-JSCO CPGs before the survey, 492 (73.0%) of whom had read all or part of the guidelines (publications 57.1%, JSMO website 34.8%, and JSCO website 14.0%). Knowledge about, attitudes toward, and barriers to adherence to each recommendation differed widely according to the clinical questions. The most commonly cited barriers were lack of awareness, lack of agreement, lack of evidence, lack of outcome expectancy, patient values and preferences, and patient factors. DiscussionThis survey identified different barriers to guideline adherence, including providers' knowledge, attitudes, and external factors, depending on each recommendation. Effective strategies to overcome these barriers can be expected to improve the implementation of the guideline recommendations. Based on the results of this survey, efforts should be made to promote further the use of the clinical guidelines in daily practice.

A hybrid caching strategy for information-centric satellite networks based on node classification and popular content awareness

Low Earth Orbit (LEO) satellite networks are inexpensive to deploy and have wide coverage, and are widely available for differentiated content distribution services. With the development of on-board storage and computing capabilities, in-network caching technology in information centric networking (ICN) has proven to be an effective way to increase the throughput and content distribution efficiency of satellite networks. However, traditional caching and distribution schemes, which do not take into account the high-speed motion of satellite nodes and dynamic changes in topology, are not applicable to satellite networks. To address these issues, a hybrid caching strategy for satellite networks based on node classification and popular content awareness (NCPCA) is proposed. Firstly, the time slot partitioning method based on interlayer similarity is proposed to transform the dynamically changing process into a set of time slots with stable topology. Next, the satellite nodes are dynamically divided into two categories by fully considering the changes in connection relationships and interaction order during the spatial–temporal evolution of the satellite nodes. Nodes with satellite topological and functional characteristics are screened out as core nodes with TOPSIS algorithm, and the remaining nodes are regarded as edge nodes. Finally, a probabilistic caching scheme based on content popularity is adopted with core nodes as caching nodes to ensure caching performance and promote the diversity of cached content. Simulation results show that this strategy can effectively improve cache hit rate, reduce user request delay and content fetching hops, and promote the stable operation of satellite networks compared with other caching strategies.

Diffusion of Technology during Covid Period

During the Covid period the people are depending broadband internet connectivity for their work. Faster and reliable connectivity is becoming an essential criterion in our daily life. The pandemic period has provided an opportunity for fast diffusion of technology. So uninterrupted and high speed data services has become essential. During the lock-down period people prefer online platforms of food distribution services for ordering food .The covid crisis has changed everything to online. People are forced to adapt to new technologies during the covid period. This article narrate consumer preference towards various broadband internet services and the diffusion of broad band internet services.

On super apps and app stores: digital media logics in China’s app economy

Aiming to enrich the conceptual vocabulary of platform and app studies, this article provides a critical political economic perspective on the media industry to understand how platform power is operationalized in the app economy. Using the China-based tech conglomerate Tencent as a case study, four mechanisms are discussed: conglomeration, financialization, platformization, and infrastructuralization. These mechanisms show how Tencent leveraged both a conglomerated corporate structure and access to finance capital. This was combined with the infrastructuralization of the MyApp app store and the WeChat platform by providing vertically integrated app development and distribution services, which are nested in Tencent’s holdings and investments. Taking Tencent as the starting point for theory building, this article attempts to “provincialize” US-based platform companies by charting Tencent’s corporate evolution and its path to mobile dominance.

Anticipating water distribution service outages from increasing temperatures

With projected temperature increases and extreme events due to climate change for many regions of the world, characterizing the impacts of these emerging hazards on water distribution systems is necessary to identify and prioritize adaptation strategies for ensuring reliability. To aid decision-making, new insights are needed into how water distribution system reliability to climate-driven heat will change, and the proactive maintenance strategies available to combat failures. To this end, we present the model Perses, a framework that joins a water distribution network hydraulic solver with reliability models of physical assets or components to estimate temperature increase-driven failures and resulting service outages in the long term. A theoretical case study is developed using Phoenix, Arizona temperature profiles, a city with extreme temperatures and a rapidly expanding infrastructure. By end-of-century under hotter futures there are projected to be 1%–5% more pump failures, 2%–5% more PVC pipe failures, and 3%–7% more iron pipe failures (RCP 4.5–8.5) than a baseline historical temperature profile. Service outages, which constitute inadequate pressure for domestic and commercial use are projected to increase by 16%–26% above the baseline under maximum temperature conditions. The exceedance of baseline failures, when compounded across a large metro region, reveals potential challenges for budgeting, management, and maintenance. An exploration of the mitigation potential of adaptation strategies shows that expedited repair times are capable of offsetting the additional outages from climate change, but will come with a cost.

Improving Metropolitan Transportation Efficiency With FAST Miles

In America’s large and severely congested metropolitan areas, carpools and express bus service could attract many more riders if they could operate between residential areas and job centers on free-flowing highways that provide premium service opportunities. FAST Miles attempts to eliminate recurring congestion on limited-access highway systems using a potentially more publicly acceptable form of road pricing, along with an integrated multimodal strategy to encourage shifts of solo-driving commuters to alternative modes. FAST Miles allocates to motorists a limited number of free miles for use in peak periods on limited-access highways. Every motorist would get a share of free peak-period use of FAST highway facilities “already paid for” through his or her taxes through free FAST Miles credits. Total outstanding credits would be limited to ensure that the metropolitan highway system does not get congested and that express bus services operate faster, providing better levels of service at a lower cost.The concept would include new express bus and carpooling services, improved passenger collection and distribution services at bus transfer stations, free transit trial periods, web-based multimodal trip-planning programs, and individualized marketing of alternative modes at employment centers and in residential areas. Preliminary sketch analysis suggests that FAST Miles could be self-financing. It also would introduce new possibilities for public-private partnerships.

Mobility-Aware Offloading and Resource Allocation for Distributed Services Collaboration

In mobile edge computing (MEC) systems, mobile users (MUs) are capable of allocating local resources (CPU frequency and transmission power) and offloading tasks to edge servers in the vicinity in order to enhance their computation capabilities and reduce back-and-forth transmission over backhaul link. Nevertheless, mobile environment makes it hard to draw offloading and resource allocation decisions under dynamical wireless channel state and users’ locations. In real life, social relationship is also provably a significant factor affecting integral performance in collaborative work, which results in MUs decisions strongly coupled and renders this problem further intractable. Most of previous works ignore the impact of inter-user dependency (or data dependency among IoT devices). To bridge this gap, we study the service collaboration with master-slave dependency among service chains of MUs and formulate this combinational optimization problem as a mixed integer non-linear programming (MINLP) problem. To this end, we derive the closed-form expression of resource allocation solution by convex optimization and transform it to integer linear programming (ILP) problem. Subsequently, we propose a distributed algorithm based on Markov approximation which has polynomial computation complexity. Experimental result on real-world dataset substantiates the usefulness and superiority of our scheme, in terms of reducing latency and energy consumption.

Last-mile delivery optimization considering the demand of market distribution methods: A case studies using Adaptive Large Neighborhood Search algorithm

Based on the current situation and problems of transportation "last mile" transportation distribution, this paper establishes a path optimization model based on user distribution methods from the perspective of market preference for transportation distribution methods, designs an Adaptive Large Neighborhood Search (ALNS) algorithm, and builds a user portrait based on the solution algorithm and the construction method. Based on the solution algorithm and the user portrait construction method, the solution scenario is established, and the distribution route and transportation distribution method are planned based on five real location data. Through the analysis of the solution scenarios, it can be obtained that after the optimization of the model, the transportation distribution cost of enterprises can be reduced, and the satisfaction of the transportation distribution service quality can be improved. The higher the complaint cost, the lower the total transportation and distribution cost, and the higher the satisfaction rate; the higher the time window penalty cost, the higher the total distribution cost, and the lower the satisfaction rate. Through several model comparisons, it is found that the optimized model has obvious advantages in transportation cost and good performance in transportation service satisfaction. To further strengthen the promotion and application of the distribution path optimization model, countermeasures are proposed in three aspects: establishing a unified end transportation information service platform, increasing the investment in end transportation path optimization, and strengthening the formulation of supporting policies to realize the optimization of end distribution services.

Efficient incentive mechanism for video distribution on the home Internet of Things devices

Providing users with nearby video distribution services based on Edge Computing (EC) reduces backbone traffic and improves users' viewing experience. However, the behavior of edge networks is difficult to manage and cannot guarantee the rationality of video resource distribution, which has become a significant challenge for online video services. This paper takes the idle resources from home Internet of Things (IoT) devices for video distribution service as the research point. It proposes an incentive mechanism based on behavior management and balance of resources (BMBR). By paying attention to the rationality of resource distribution and establishing reasonable reward and punishment measures for edge devices, the incentive mechanism makes the initiative of edge devices and the relationship between resource supply and demand reach a stable equilibrium. Simulation results and analysis show that the incentive mechanism can effectively improve the enthusiasm for resource sharing in the edge network, ensure the rationality of resource distribution to reduce the resource price fluctuations, and maintain the balance of resource supply and demand.